LEMON/LEMON-main Changeset - r540:9db62975c32b

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Changeset - r540:9db62975c32b

« 539:547e96

541:89e29e »

r540:9db62975c32b

Thu, 26 Feb 2009 08:39:16

[Not Reviewed]

0 comments (0 inline)

alpar (Alpar Juttner)
alpar@cs.elte.hu

Fix newSolver()/cloneSolver() API in LP tools + doc improvements (#230) - More logical structure for newSolver()/cloneSolver() - Fix compilation problem with gcc-3.3 - Doc improvements

0 13 0

default

13 files changed with 118 insertions and 78 deletions:

lemon/clp.cc

lemon/clp.h

lemon/cplex.cc

lemon/cplex.h

lemon/glpk.cc

lemon/glpk.h

lemon/lp_base.h

lemon/lp_skeleton.cc

lemon/lp_skeleton.h

lemon/soplex.cc

lemon/soplex.h

test/lp_test.cc

test/mip_test.cc

↑ Collapse diff ↑

lemon/clp.cc

Show inline comments

/* -*- mode: C++; indent-tabs-mode: nil; -*-
 *
 * This file is a part of LEMON, a generic C++ optimization library.
 *
 * Copyright (C) 2003-2008
 * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
 * (Egervary Research Group on Combinatorial Optimization, EGRES).
 *
 * Permission to use, modify and distribute this software is granted
 * provided that this copyright notice appears in all copies. For
 * precise terms see the accompanying LICENSE file.
 *
 * This software is provided "AS IS" with no warranty of any kind,
 * express or implied, and with no claim as to its suitability for any
 * purpose.
 *
 */

#include <lemon/clp.h>
#include <coin/ClpSimplex.hpp>

namespace lemon {

  ClpLp::ClpLp() {
    _prob = new ClpSimplex();
    _init_temporals();
    messageLevel(MESSAGE_NO_OUTPUT);
  }

  ClpLp::ClpLp(const ClpLp& other) {
    _prob = new ClpSimplex(*other._prob);
    rows = other.rows;
    cols = other.cols;
    _init_temporals();
    messageLevel(MESSAGE_NO_OUTPUT);
  }

  ClpLp::~ClpLp() {
    delete _prob;
    _clear_temporals();
  }

  void ClpLp::_init_temporals() {
    _primal_ray = 0;
    _dual_ray = 0;
  }

  void ClpLp::_clear_temporals() {
    if (_primal_ray) {
      delete[] _primal_ray;
      _primal_ray = 0;
    }
    if (_dual_ray) {
      delete[] _dual_ray;
      _dual_ray = 0;
    }
  }

  ClpLp* ClpLp::_newSolver() const {
  ClpLp* ClpLp::newSolver() const {
    ClpLp* newlp = new ClpLp;
    return newlp;
  }

  ClpLp* ClpLp::_cloneSolver() const {
  ClpLp* ClpLp::cloneSolver() const {
    ClpLp* copylp = new ClpLp(*this);
    return copylp;
  }

  const char* ClpLp::_solverName() const { return "ClpLp"; }

  int ClpLp::_addCol() {
    _prob->addColumn(0, 0, 0, -COIN_DBL_MAX, COIN_DBL_MAX, 0.0);
    return _prob->numberColumns() - 1;
  }

  int ClpLp::_addRow() {
    _prob->addRow(0, 0, 0, -COIN_DBL_MAX, COIN_DBL_MAX);
    return _prob->numberRows() - 1;
  }


  void ClpLp::_eraseCol(int c) {
    _col_names_ref.erase(_prob->getColumnName(c));
    _prob->deleteColumns(1, &c);
  }

  void ClpLp::_eraseRow(int r) {
    _row_names_ref.erase(_prob->getRowName(r));
    _prob->deleteRows(1, &r);
  }

  void ClpLp::_eraseColId(int i) {
    cols.eraseIndex(i);
    cols.shiftIndices(i);
  }

  void ClpLp::_eraseRowId(int i) {
    rows.eraseIndex(i);
    rows.shiftIndices(i);
  }

  void ClpLp::_getColName(int c, std::string& name) const {
    name = _prob->getColumnName(c);
  }

  void ClpLp::_setColName(int c, const std::string& name) {
    _prob->setColumnName(c, const_cast<std::string&>(name));
    _col_names_ref[name] = c;
  }

  int ClpLp::_colByName(const std::string& name) const {
    std::map<std::string, int>::const_iterator it = _col_names_ref.find(name);
    return it != _col_names_ref.end() ? it->second : -1;
  }

  void ClpLp::_getRowName(int r, std::string& name) const {
    name = _prob->getRowName(r);
  }

  void ClpLp::_setRowName(int r, const std::string& name) {
    _prob->setRowName(r, const_cast<std::string&>(name));
    _row_names_ref[name] = r;
  }

  int ClpLp::_rowByName(const std::string& name) const {
    std::map<std::string, int>::const_iterator it = _row_names_ref.find(name);
    return it != _row_names_ref.end() ? it->second : -1;
  }


  void ClpLp::_setRowCoeffs(int ix, ExprIterator b, ExprIterator e) {
    std::map<int, Value> coeffs;

    int n = _prob->clpMatrix()->getNumCols();

    const int* indices = _prob->clpMatrix()->getIndices();
    const double* elements = _prob->clpMatrix()->getElements();

    for (int i = 0; i < n; ++i) {
      CoinBigIndex begin = _prob->clpMatrix()->getVectorStarts()[i];
      CoinBigIndex end = begin + _prob->clpMatrix()->getVectorLengths()[i];

      const int* it = std::lower_bound(indices + begin, indices + end, ix);
      if (it != indices + end && *it == ix && elements[it - indices] != 0.0) {
        coeffs[i] = 0.0;
      }
    }

    for (ExprIterator it = b; it != e; ++it) {
      coeffs[it->first] = it->second;
    }

    for (std::map<int, Value>::iterator it = coeffs.begin();
         it != coeffs.end(); ++it) {
      _prob->modifyCoefficient(ix, it->first, it->second);
    }
  }

  void ClpLp::_getRowCoeffs(int ix, InsertIterator b) const {
    int n = _prob->clpMatrix()->getNumCols();

    const int* indices = _prob->clpMatrix()->getIndices();
    const double* elements = _prob->clpMatrix()->getElements();

    for (int i = 0; i < n; ++i) {
      CoinBigIndex begin = _prob->clpMatrix()->getVectorStarts()[i];
      CoinBigIndex end = begin + _prob->clpMatrix()->getVectorLengths()[i];

      const int* it = std::lower_bound(indices + begin, indices + end, ix);
      if (it != indices + end && *it == ix) {
        *b = std::make_pair(i, elements[it - indices]);
      }
    }
  }

  void ClpLp::_setColCoeffs(int ix, ExprIterator b, ExprIterator e) {
    std::map<int, Value> coeffs;

    CoinBigIndex begin = _prob->clpMatrix()->getVectorStarts()[ix];
    CoinBigIndex end = begin + _prob->clpMatrix()->getVectorLengths()[ix];

    const int* indices = _prob->clpMatrix()->getIndices();
    const double* elements = _prob->clpMatrix()->getElements();

    for (CoinBigIndex i = begin; i != end; ++i) {
      if (elements[i] != 0.0) {
        coeffs[indices[i]] = 0.0;
      }
    }
    for (ExprIterator it = b; it != e; ++it) {
      coeffs[it->first] = it->second;
    }
    for (std::map<int, Value>::iterator it = coeffs.begin();
         it != coeffs.end(); ++it) {
      _prob->modifyCoefficient(it->first, ix, it->second);
    }
  }

  void ClpLp::_getColCoeffs(int ix, InsertIterator b) const {
    CoinBigIndex begin = _prob->clpMatrix()->getVectorStarts()[ix];
    CoinBigIndex end = begin + _prob->clpMatrix()->getVectorLengths()[ix];

    const int* indices = _prob->clpMatrix()->getIndices();
    const double* elements = _prob->clpMatrix()->getElements();

    for (CoinBigIndex i = begin; i != end; ++i) {
      *b = std::make_pair(indices[i], elements[i]);
      ++b;
    }
  }

  void ClpLp::_setCoeff(int ix, int jx, Value value) {
    _prob->modifyCoefficient(ix, jx, value);
  }

  ClpLp::Value ClpLp::_getCoeff(int ix, int jx) const {
    CoinBigIndex begin = _prob->clpMatrix()->getVectorStarts()[ix];
    CoinBigIndex end = begin + _prob->clpMatrix()->getVectorLengths()[ix];

    const int* indices = _prob->clpMatrix()->getIndices();
    const double* elements = _prob->clpMatrix()->getElements();

    const int* it = std::lower_bound(indices + begin, indices + end, jx);
    if (it != indices + end && *it == jx) {
      return elements[it - indices];
    } else {
      return 0.0;
    }
  }

  void ClpLp::_setColLowerBound(int i, Value lo) {
    _prob->setColumnLower(i, lo == - INF ? - COIN_DBL_MAX : lo);
  }

  ClpLp::Value ClpLp::_getColLowerBound(int i) const {
    double val = _prob->getColLower()[i];
    return val == - COIN_DBL_MAX ? - INF : val;
  }

  void ClpLp::_setColUpperBound(int i, Value up) {
    _prob->setColumnUpper(i, up == INF ? COIN_DBL_MAX : up);
  }

  ClpLp::Value ClpLp::_getColUpperBound(int i) const {
    double val = _prob->getColUpper()[i];
    return val == COIN_DBL_MAX ? INF : val;
  }

  void ClpLp::_setRowLowerBound(int i, Value lo) {
    _prob->setRowLower(i, lo == - INF ? - COIN_DBL_MAX : lo);
  }

  ClpLp::Value ClpLp::_getRowLowerBound(int i) const {
    double val = _prob->getRowLower()[i];
    return val == - COIN_DBL_MAX ? - INF : val;
  }

lemon/clp.h

Show inline comments

 		/* -*- mode: C++; indent-tabs-mode: nil; -*-
+		 *
 		 * This file is a part of LEMON, a generic C++ optimization library.
+		 *
 		 * Copyright (C) 2003-2008
 		 * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
 		 * (Egervary Research Group on Combinatorial Optimization, EGRES).
+		 *
 		 * Permission to use, modify and distribute this software is granted
 		 * provided that this copyright notice appears in all copies. For
 		 * precise terms see the accompanying LICENSE file.
+		 *
 		 * This software is provided "AS IS" with no warranty of any kind,
 		 * express or implied, and with no claim as to its suitability for any
 		 * purpose.
+		 *
 		 */
 		#ifndef LEMON_CLP_H
 		#define LEMON_CLP_H
 		///\file
 		///\brief Header of the LEMON-CLP lp solver interface.
 		#include <vector>
 		#include <string>
 		#include <lemon/lp_base.h>
 		class ClpSimplex;
 		namespace lemon {
 		  /// \ingroup lp_group
 		  ///
 		  /// \brief Interface for the CLP solver
 		  ///
 		  /// This class implements an interface for the Clp LP solver.  The
 		  /// Clp library is an object oriented lp solver library developed at
 		  /// the IBM. The CLP is part of the COIN-OR package and it can be
 		  /// used with Common Public License.
 		  class ClpLp : public LpSolver {
 		  protected:
 		    ClpSimplex* _prob;
 		    std::map<std::string, int> _col_names_ref;
 		    std::map<std::string, int> _row_names_ref;
 		  public:
 		    /// \e
 		    ClpLp();
 		    /// \e
 		    ClpLp(const ClpLp&);
 		    /// \e
 		    ~ClpLp();
 		    /// \e
 		    virtual ClpLp* newSolver() const;
 		    /// \e
 		    virtual ClpLp* cloneSolver() const;
 		  protected:
 		    mutable double* _primal_ray;
 		    mutable double* _dual_ray;
 		    void _init_temporals();
 		    void _clear_temporals();
 		  protected:
 		    virtual ClpLp* _newSolver() const;
 		    virtual ClpLp* _cloneSolver() const;
 		    virtual const char* _solverName() const;
 		    virtual int _addCol();
 		    virtual int _addRow();
 		    virtual void _eraseCol(int i);
 		    virtual void _eraseRow(int i);
 		    virtual void _eraseColId(int i);
 		    virtual void _eraseRowId(int i);
 		    virtual void _getColName(int col, std::string& name) const;
 		    virtual void _setColName(int col, const std::string& name);
 		    virtual int _colByName(const std::string& name) const;
 		    virtual void _getRowName(int row, std::string& name) const;
 		    virtual void _setRowName(int row, const std::string& name);
 		    virtual int _rowByName(const std::string& name) const;
 		    virtual void _setRowCoeffs(int i, ExprIterator b, ExprIterator e);
 		    virtual void _getRowCoeffs(int i, InsertIterator b) const;
 		    virtual void _setColCoeffs(int i, ExprIterator b, ExprIterator e);
 		    virtual void _getColCoeffs(int i, InsertIterator b) const;
 		    virtual void _setCoeff(int row, int col, Value value);
 		    virtual Value _getCoeff(int row, int col) const;
 		    virtual void _setColLowerBound(int i, Value value);
 		    virtual Value _getColLowerBound(int i) const;
 		    virtual void _setColUpperBound(int i, Value value);
 		    virtual Value _getColUpperBound(int i) const;
 		    virtual void _setRowLowerBound(int i, Value value);
 		    virtual Value _getRowLowerBound(int i) const;
 		    virtual void _setRowUpperBound(int i, Value value);
 		    virtual Value _getRowUpperBound(int i) const;
 		    virtual void _setObjCoeffs(ExprIterator, ExprIterator);
 		    virtual void _getObjCoeffs(InsertIterator) const;
 		    virtual void _setObjCoeff(int i, Value obj_coef);
 		    virtual Value _getObjCoeff(int i) const;
 		    virtual void _setSense(Sense sense);
 		    virtual Sense _getSense() const;
 		    virtual SolveExitStatus _solve();
 		    virtual Value _getPrimal(int i) const;
 		    virtual Value _getDual(int i) const;
 		    virtual Value _getPrimalValue() const;
 		    virtual Value _getPrimalRay(int i) const;
 		    virtual Value _getDualRay(int i) const;
 		    virtual VarStatus _getColStatus(int i) const;
 		    virtual VarStatus _getRowStatus(int i) const;
 		    virtual ProblemType _getPrimalType() const;
 		    virtual ProblemType _getDualType() const;
 		    virtual void _clear();
 		  public:
 		    ///Solves LP with primal simplex method.
 		    SolveExitStatus solvePrimal();
 		    ///Solves LP with dual simplex method.
 		    SolveExitStatus solveDual();
 		    ///Solves LP with barrier method.
 		    SolveExitStatus solveBarrier();
 		    ///Returns the constraint identifier understood by CLP.
 		    int clpRow(Row r) const { return rows(id(r)); }
 		    ///Returns the variable identifier understood by CLP.
 		    int clpCol(Col c) const { return cols(id(c)); }
 		    ///Enum for \c messageLevel() parameter
 		    enum MessageLevel {
 		      /// no output (default value)
 		      MESSAGE_NO_OUTPUT = 0,
 		      /// print final solution
 		      MESSAGE_FINAL_SOLUTION = 1,
 		      /// print factorization
 		      MESSAGE_FACTORIZATION = 2,
 		      /// normal output
 		      MESSAGE_NORMAL_OUTPUT = 3,
 		      /// verbose output
 		      MESSAGE_VERBOSE_OUTPUT = 4
 		    };
 		    ///Set the verbosity of the messages
 		    ///Set the verbosity of the messages
 		    ///
 		    ///\param m is the level of the messages output by the solver routines.
 		    void messageLevel(MessageLevel m);
 		  };
 		} //END OF NAMESPACE LEMON
 		#endif //LEMON_CLP_H

lemon/cplex.cc

Show inline comments

@@ -262,664 +262,664 @@
 		  void CplexBase::_setCoeff(int row, int col, Value value) {
 		    CPXchgcoef(cplexEnv(), _prob, row, col, value);
+		  }
 		  CplexBase::Value CplexBase::_getCoeff(int row, int col) const {
 		    CplexBase::Value value;
 		    CPXgetcoef(cplexEnv(), _prob, row, col, &value);
 		    return value;
+		  }
 		  void CplexBase::_setColLowerBound(int i, Value value) {
 		    const char s = 'L';
 		    CPXchgbds(cplexEnv(), _prob, 1, &i, &s, &value);
+		  }
 		  CplexBase::Value CplexBase::_getColLowerBound(int i) const {
 		    CplexBase::Value res;
 		    CPXgetlb(cplexEnv(), _prob, &res, i, i);
 		    return res <= -CPX_INFBOUND ? -INF : res;
+		  }
 		  void CplexBase::_setColUpperBound(int i, Value value)
+		  {
 		    const char s = 'U';
 		    CPXchgbds(cplexEnv(), _prob, 1, &i, &s, &value);
+		  }
 		  CplexBase::Value CplexBase::_getColUpperBound(int i) const {
 		    CplexBase::Value res;
 		    CPXgetub(cplexEnv(), _prob, &res, i, i);
 		    return res >= CPX_INFBOUND ? INF : res;
+		  }
 		  CplexBase::Value CplexBase::_getRowLowerBound(int i) const {
 		    char s;
 		    CPXgetsense(cplexEnv(), _prob, &s, i, i);
 		    CplexBase::Value res;
 		    switch (s) {
 		    case 'G':
 		    case 'R':
 		    case 'E':
 		      CPXgetrhs(cplexEnv(), _prob, &res, i, i);
 		      return res <= -CPX_INFBOUND ? -INF : res;
 		    default:
 		      return -INF;
+		    }
+		  }
 		  CplexBase::Value CplexBase::_getRowUpperBound(int i) const {
 		    char s;
 		    CPXgetsense(cplexEnv(), _prob, &s, i, i);
 		    CplexBase::Value res;
 		    switch (s) {
 		    case 'L':
 		    case 'E':
 		      CPXgetrhs(cplexEnv(), _prob, &res, i, i);
 		      return res >= CPX_INFBOUND ? INF : res;
 		    case 'R':
 		      CPXgetrhs(cplexEnv(), _prob, &res, i, i);
+		      {
 		        double rng;
 		        CPXgetrngval(cplexEnv(), _prob, &rng, i, i);
 		        res += rng;
+		      }
 		      return res >= CPX_INFBOUND ? INF : res;
 		    default:
 		      return INF;
+		    }
+		  }
 		  //This is easier to implement
 		  void CplexBase::_set_row_bounds(int i, Value lb, Value ub) {
 		    if (lb == -INF) {
 		      const char s = 'L';
 		      CPXchgsense(cplexEnv(), _prob, 1, &i, &s);
 		      CPXchgrhs(cplexEnv(), _prob, 1, &i, &ub);
 		    } else if (ub == INF) {
 		      const char s = 'G';
 		      CPXchgsense(cplexEnv(), _prob, 1, &i, &s);
 		      CPXchgrhs(cplexEnv(), _prob, 1, &i, &lb);
 		    } else if (lb == ub){
 		      const char s = 'E';
 		      CPXchgsense(cplexEnv(), _prob, 1, &i, &s);
 		      CPXchgrhs(cplexEnv(), _prob, 1, &i, &lb);
 		    } else {
 		      const char s = 'R';
 		      CPXchgsense(cplexEnv(), _prob, 1, &i, &s);
 		      CPXchgrhs(cplexEnv(), _prob, 1, &i, &lb);
 		      double len = ub - lb;
 		      CPXchgrngval(cplexEnv(), _prob, 1, &i, &len);
+		    }
+		  }
 		  void CplexBase::_setRowLowerBound(int i, Value lb)
+		  {
 		    LEMON_ASSERT(lb != INF, "Invalid bound");
 		    _set_row_bounds(i, lb, CplexBase::_getRowUpperBound(i));
+		  }
 		  void CplexBase::_setRowUpperBound(int i, Value ub)
+		  {
 		    LEMON_ASSERT(ub != -INF, "Invalid bound");
 		    _set_row_bounds(i, CplexBase::_getRowLowerBound(i), ub);
+		  }
 		  void CplexBase::_setObjCoeffs(ExprIterator b, ExprIterator e)
+		  {
 		    std::vector<int> indices;
 		    std::vector<Value> values;
 		    for(ExprIterator it=b; it!=e; ++it) {
 		      indices.push_back(it->first);
 		      values.push_back(it->second);
+		    }
 		    CPXchgobj(cplexEnv(), _prob, values.size(),
 		              &indices.front(), &values.front());
+		  }
 		  void CplexBase::_getObjCoeffs(InsertIterator b) const
+		  {
 		    int num = CPXgetnumcols(cplexEnv(), _prob);
 		    std::vector<Value> x(num);
 		    CPXgetobj(cplexEnv(), _prob, &x.front(), 0, num - 1);
 		    for (int i = 0; i < num; ++i) {
 		      if (x[i] != 0.0) {
 		        *b = std::make_pair(i, x[i]);
 		        ++b;
+		      }
+		    }
+		  }
 		  void CplexBase::_setObjCoeff(int i, Value obj_coef)
+		  {
 		    CPXchgobj(cplexEnv(), _prob, 1, &i, &obj_coef);
+		  }
 		  CplexBase::Value CplexBase::_getObjCoeff(int i) const
+		  {
 		    Value x;
 		    CPXgetobj(cplexEnv(), _prob, &x, i, i);
 		    return x;
+		  }
 		  void CplexBase::_setSense(CplexBase::Sense sense) {
 		    switch (sense) {
 		    case MIN:
 		      CPXchgobjsen(cplexEnv(), _prob, CPX_MIN);
 		      break;
 		    case MAX:
 		      CPXchgobjsen(cplexEnv(), _prob, CPX_MAX);
 		      break;
+		    }
+		  }
 		  CplexBase::Sense CplexBase::_getSense() const {
 		    switch (CPXgetobjsen(cplexEnv(), _prob)) {
 		    case CPX_MIN:
 		      return MIN;
 		    case CPX_MAX:
 		      return MAX;
 		    default:
 		      LEMON_ASSERT(false, "Invalid sense");
 		      return CplexBase::Sense();
+		    }
+		  }
 		  void CplexBase::_clear() {
 		    CPXfreeprob(cplexEnv(),&_prob);
 		    int status;
 		    _prob = CPXcreateprob(cplexEnv(), &status, "Cplex problem");
 		    rows.clear();
 		    cols.clear();
+		  }
 		  // CplexLp members
 		  CplexLp::CplexLp()
 		    : LpBase(), CplexBase(), LpSolver() {}
 		  CplexLp::CplexLp(const CplexEnv& env)
 		    : LpBase(), CplexBase(env), LpSolver() {}
 		  CplexLp::CplexLp(const CplexLp& other)
 		    : LpBase(), CplexBase(other), LpSolver() {}
 		  CplexLp::~CplexLp() {}
 		  CplexLp* CplexLp::_newSolver() const { return new CplexLp; }
 		  CplexLp* CplexLp::_cloneSolver() const {return new CplexLp(*this); }
 		  CplexLp* CplexLp::newSolver() const { return new CplexLp; }
 		  CplexLp* CplexLp::cloneSolver() const {return new CplexLp(*this); }
 		  const char* CplexLp::_solverName() const { return "CplexLp"; }
 		  void CplexLp::_clear_temporals() {
 		    _col_status.clear();
 		    _row_status.clear();
 		    _primal_ray.clear();
 		    _dual_ray.clear();
+		  }
 		  // The routine returns zero unless an error occurred during the
 		  // optimization. Examples of errors include exhausting available
 		  // memory (CPXERR_NO_MEMORY) or encountering invalid data in the
 		  // CPLEX problem object (CPXERR_NO_PROBLEM). Exceeding a
 		  // user-specified CPLEX limit, or proving the model infeasible or
 		  // unbounded, are not considered errors. Note that a zero return
 		  // value does not necessarily mean that a solution exists. Use query
 		  // routines CPXsolninfo, CPXgetstat, and CPXsolution to obtain
 		  // further information about the status of the optimization.
 		  CplexLp::SolveExitStatus CplexLp::convertStatus(int status) {
 		#if CPX_VERSION >= 800
 		    if (status == 0) {
 		      switch (CPXgetstat(cplexEnv(), _prob)) {
 		      case CPX_STAT_OPTIMAL:
 		      case CPX_STAT_INFEASIBLE:
 		      case CPX_STAT_UNBOUNDED:
 		        return SOLVED;
 		      default:
 		        return UNSOLVED;
+		      }
 		    } else {
 		      return UNSOLVED;
+		    }
 		#else
 		    if (status == 0) {
 		      //We want to exclude some cases
 		      switch (CPXgetstat(cplexEnv(), _prob)) {
 		      case CPX_OBJ_LIM:
 		      case CPX_IT_LIM_FEAS:
 		      case CPX_IT_LIM_INFEAS:
 		      case CPX_TIME_LIM_FEAS:
 		      case CPX_TIME_LIM_INFEAS:
 		        return UNSOLVED;
 		      default:
 		        return SOLVED;
+		      }
 		    } else {
 		      return UNSOLVED;
+		    }
 		#endif
+		  }
 		  CplexLp::SolveExitStatus CplexLp::_solve() {
 		    _clear_temporals();
 		    return convertStatus(CPXlpopt(cplexEnv(), _prob));
+		  }
 		  CplexLp::SolveExitStatus CplexLp::solvePrimal() {
 		    _clear_temporals();
 		    return convertStatus(CPXprimopt(cplexEnv(), _prob));
+		  }
 		  CplexLp::SolveExitStatus CplexLp::solveDual() {
 		    _clear_temporals();
 		    return convertStatus(CPXdualopt(cplexEnv(), _prob));
+		  }
 		  CplexLp::SolveExitStatus CplexLp::solveBarrier() {
 		    _clear_temporals();
 		    return convertStatus(CPXbaropt(cplexEnv(), _prob));
+		  }
 		  CplexLp::Value CplexLp::_getPrimal(int i) const {
 		    Value x;
 		    CPXgetx(cplexEnv(), _prob, &x, i, i);
 		    return x;
+		  }
 		  CplexLp::Value CplexLp::_getDual(int i) const {
 		    Value y;
 		    CPXgetpi(cplexEnv(), _prob, &y, i, i);
 		    return y;
+		  }
 		  CplexLp::Value CplexLp::_getPrimalValue() const {
 		    Value objval;
 		    CPXgetobjval(cplexEnv(), _prob, &objval);
 		    return objval;
+		  }
 		  CplexLp::VarStatus CplexLp::_getColStatus(int i) const {
 		    if (_col_status.empty()) {
 		      _col_status.resize(CPXgetnumcols(cplexEnv(), _prob));
 		      CPXgetbase(cplexEnv(), _prob, &_col_status.front(), 0);
+		    }
 		    switch (_col_status[i]) {
 		    case CPX_BASIC:
 		      return BASIC;
 		    case CPX_FREE_SUPER:
 		      return FREE;
 		    case CPX_AT_LOWER:
 		      return LOWER;
 		    case CPX_AT_UPPER:
 		      return UPPER;
 		    default:
 		      LEMON_ASSERT(false, "Wrong column status");
 		      return CplexLp::VarStatus();
+		    }
+		  }
 		  CplexLp::VarStatus CplexLp::_getRowStatus(int i) const {
 		    if (_row_status.empty()) {
 		      _row_status.resize(CPXgetnumrows(cplexEnv(), _prob));
 		      CPXgetbase(cplexEnv(), _prob, 0, &_row_status.front());
+		    }
 		    switch (_row_status[i]) {
 		    case CPX_BASIC:
 		      return BASIC;
 		    case CPX_AT_LOWER:
+		      {
 		        char s;
 		        CPXgetsense(cplexEnv(), _prob, &s, i, i);
 		        return s != 'L' ? LOWER : UPPER;
+		      }
 		    case CPX_AT_UPPER:
 		      return UPPER;
 		    default:
 		      LEMON_ASSERT(false, "Wrong row status");
 		      return CplexLp::VarStatus();
+		    }
+		  }
 		  CplexLp::Value CplexLp::_getPrimalRay(int i) const {
 		    if (_primal_ray.empty()) {
 		      _primal_ray.resize(CPXgetnumcols(cplexEnv(), _prob));
 		      CPXgetray(cplexEnv(), _prob, &_primal_ray.front());
+		    }
 		    return _primal_ray[i];
+		  }
 		  CplexLp::Value CplexLp::_getDualRay(int i) const {
 		    if (_dual_ray.empty()) {
+		    }
 		    return _dual_ray[i];
+		  }
 		  //7.5-os cplex statusai (Vigyazat: a 9.0-asei masok!)
 		  // This table lists the statuses, returned by the CPXgetstat()
 		  // routine, for solutions to LP problems or mixed integer problems. If
 		  // no solution exists, the return value is zero.
 		  // For Simplex, Barrier
 		  // 1          CPX_OPTIMAL
 		  //          Optimal solution found
 		  // 2          CPX_INFEASIBLE
 		  //          Problem infeasible
 		  // 3    CPX_UNBOUNDED
 		  //          Problem unbounded
 		  // 4          CPX_OBJ_LIM
 		  //          Objective limit exceeded in Phase II
 		  // 5          CPX_IT_LIM_FEAS
 		  //          Iteration limit exceeded in Phase II
 		  // 6          CPX_IT_LIM_INFEAS
 		  //          Iteration limit exceeded in Phase I
 		  // 7          CPX_TIME_LIM_FEAS
 		  //          Time limit exceeded in Phase II
 		  // 8          CPX_TIME_LIM_INFEAS
 		  //          Time limit exceeded in Phase I
 		  // 9          CPX_NUM_BEST_FEAS
 		  //          Problem non-optimal, singularities in Phase II
 		  // 10         CPX_NUM_BEST_INFEAS
 		  //          Problem non-optimal, singularities in Phase I
 		  // 11         CPX_OPTIMAL_INFEAS
 		  //          Optimal solution found, unscaled infeasibilities
 		  // 12         CPX_ABORT_FEAS
 		  //          Aborted in Phase II
 		  // 13         CPX_ABORT_INFEAS
 		  //          Aborted in Phase I
 		  // 14          CPX_ABORT_DUAL_INFEAS
 		  //          Aborted in barrier, dual infeasible
 		  // 15          CPX_ABORT_PRIM_INFEAS
 		  //          Aborted in barrier, primal infeasible
 		  // 16          CPX_ABORT_PRIM_DUAL_INFEAS
 		  //          Aborted in barrier, primal and dual infeasible
 		  // 17          CPX_ABORT_PRIM_DUAL_FEAS
 		  //          Aborted in barrier, primal and dual feasible
 		  // 18          CPX_ABORT_CROSSOVER
 		  //          Aborted in crossover
 		  // 19          CPX_INForUNBD
 		  //          Infeasible or unbounded
 		  // 20   CPX_PIVOT
 		  //       User pivot used
 		  //
 		  //     Ezeket hova tegyem:
 		  // ??case CPX_ABORT_DUAL_INFEAS
 		  // ??case CPX_ABORT_CROSSOVER
 		  // ??case CPX_INForUNBD
 		  // ??case CPX_PIVOT
 		  //Some more interesting stuff:
 		  // CPX_PARAM_PROBMETHOD  1062  int  LPMETHOD
 		  // 0 Automatic
 		  // 1 Primal Simplex
 		  // 2 Dual Simplex
 		  // 3 Network Simplex
 		  // 4 Standard Barrier
 		  // Default: 0
 		  // Description: Method for linear optimization.
 		  // Determines which algorithm is used when CPXlpopt() (or "optimize"
 		  // in the Interactive Optimizer) is called. Currently the behavior of
 		  // the "Automatic" setting is that CPLEX simply invokes the dual
 		  // simplex method, but this capability may be expanded in the future
 		  // so that CPLEX chooses the method based on problem characteristics
 		#if CPX_VERSION < 900
 		  void statusSwitch(CPXENVptr cplexEnv(),int& stat){
 		    int lpmethod;
 		    CPXgetintparam (cplexEnv(),CPX_PARAM_PROBMETHOD,&lpmethod);
 		    if (lpmethod==2){
 		      if (stat==CPX_UNBOUNDED){
 		        stat=CPX_INFEASIBLE;
+		      }
 		      else{
 		        if (stat==CPX_INFEASIBLE)
 		          stat=CPX_UNBOUNDED;
+		      }
+		    }
+		  }
 		#else
 		  void statusSwitch(CPXENVptr,int&){}
 		#endif
 		  CplexLp::ProblemType CplexLp::_getPrimalType() const {
 		    // Unboundedness not treated well: the following is from cplex 9.0 doc
 		    // About Unboundedness
 		    // The treatment of models that are unbounded involves a few
 		    // subtleties. Specifically, a declaration of unboundedness means that
 		    // ILOG CPLEX has determined that the model has an unbounded
 		    // ray. Given any feasible solution x with objective z, a multiple of
 		    // the unbounded ray can be added to x to give a feasible solution
 		    // with objective z-1 (or z+1 for maximization models). Thus, if a
 		    // feasible solution exists, then the optimal objective is
 		    // unbounded. Note that ILOG CPLEX has not necessarily concluded that
 		    // a feasible solution exists. Users can call the routine CPXsolninfo
 		    // to determine whether ILOG CPLEX has also concluded that the model
 		    // has a feasible solution.
 		    int stat = CPXgetstat(cplexEnv(), _prob);
 		#if CPX_VERSION >= 800
 		    switch (stat)
+		      {
 		      case CPX_STAT_OPTIMAL:
 		        return OPTIMAL;
 		      case CPX_STAT_UNBOUNDED:
 		        return UNBOUNDED;
 		      case CPX_STAT_INFEASIBLE:
 		        return INFEASIBLE;
 		      default:
 		        return UNDEFINED;
+		      }
 		#else
 		    statusSwitch(cplexEnv(),stat);
 		    //CPXgetstat(cplexEnv(), _prob);
 		    //printf("A primal status: %d, CPX_OPTIMAL=%d \n",stat,CPX_OPTIMAL);
 		    switch (stat) {
 		    case 0:
 		      return UNDEFINED; //Undefined
 		    case CPX_OPTIMAL://Optimal
 		      return OPTIMAL;
 		    case CPX_UNBOUNDED://Unbounded
 		      return INFEASIBLE;//In case of dual simplex
 		      //return UNBOUNDED;
 		    case CPX_INFEASIBLE://Infeasible
 		      //    case CPX_IT_LIM_INFEAS:
 		      //     case CPX_TIME_LIM_INFEAS:
 		      //     case CPX_NUM_BEST_INFEAS:
 		      //     case CPX_OPTIMAL_INFEAS:
 		      //     case CPX_ABORT_INFEAS:
 		      //     case CPX_ABORT_PRIM_INFEAS:
 		      //     case CPX_ABORT_PRIM_DUAL_INFEAS:
 		      return UNBOUNDED;//In case of dual simplex
 		      //return INFEASIBLE;
 		      //     case CPX_OBJ_LIM:
 		      //     case CPX_IT_LIM_FEAS:
 		      //     case CPX_TIME_LIM_FEAS:
 		      //     case CPX_NUM_BEST_FEAS:
 		      //     case CPX_ABORT_FEAS:
 		      //     case CPX_ABORT_PRIM_DUAL_FEAS:
 		      //       return FEASIBLE;
 		    default:
 		      return UNDEFINED; //Everything else comes here
 		      //FIXME error
+		    }
 		#endif
+		  }
 		  //9.0-as cplex verzio statusai
 		  // CPX_STAT_ABORT_DUAL_OBJ_LIM
 		  // CPX_STAT_ABORT_IT_LIM
 		  // CPX_STAT_ABORT_OBJ_LIM
 		  // CPX_STAT_ABORT_PRIM_OBJ_LIM
 		  // CPX_STAT_ABORT_TIME_LIM
 		  // CPX_STAT_ABORT_USER
 		  // CPX_STAT_FEASIBLE_RELAXED
 		  // CPX_STAT_INFEASIBLE
 		  // CPX_STAT_INForUNBD
 		  // CPX_STAT_NUM_BEST
 		  // CPX_STAT_OPTIMAL
 		  // CPX_STAT_OPTIMAL_FACE_UNBOUNDED
 		  // CPX_STAT_OPTIMAL_INFEAS
 		  // CPX_STAT_OPTIMAL_RELAXED
 		  // CPX_STAT_UNBOUNDED
 		  CplexLp::ProblemType CplexLp::_getDualType() const {
 		    int stat = CPXgetstat(cplexEnv(), _prob);
 		#if CPX_VERSION >= 800
 		    switch (stat) {
 		    case CPX_STAT_OPTIMAL:
 		      return OPTIMAL;
 		    case CPX_STAT_UNBOUNDED:
 		      return INFEASIBLE;
 		    default:
 		      return UNDEFINED;
+		    }
 		#else
 		    statusSwitch(cplexEnv(),stat);
 		    switch (stat) {
 		    case 0:
 		      return UNDEFINED; //Undefined
 		    case CPX_OPTIMAL://Optimal
 		      return OPTIMAL;
 		    case CPX_UNBOUNDED:
 		      return INFEASIBLE;
 		    default:
 		      return UNDEFINED; //Everything else comes here
 		      //FIXME error
+		    }
 		#endif
+		  }
 		  // CplexMip members
 		  CplexMip::CplexMip()
 		    : LpBase(), CplexBase(), MipSolver() {
 		#if CPX_VERSION < 800
 		    CPXchgprobtype(cplexEnv(),  _prob, CPXPROB_MIP);
 		#else
 		    CPXchgprobtype(cplexEnv(),  _prob, CPXPROB_MILP);
 		#endif
+		  }
 		  CplexMip::CplexMip(const CplexEnv& env)
 		    : LpBase(), CplexBase(env), MipSolver() {
 		#if CPX_VERSION < 800
 		    CPXchgprobtype(cplexEnv(),  _prob, CPXPROB_MIP);
 		#else
 		    CPXchgprobtype(cplexEnv(),  _prob, CPXPROB_MILP);
 		#endif
+		  }
 		  CplexMip::CplexMip(const CplexMip& other)
 		    : LpBase(), CplexBase(other), MipSolver() {}
 		  CplexMip::~CplexMip() {}
 		  CplexMip* CplexMip::_newSolver() const { return new CplexMip; }
 		  CplexMip* CplexMip::_cloneSolver() const {return new CplexMip(*this); }
 		  CplexMip* CplexMip::newSolver() const { return new CplexMip; }
 		  CplexMip* CplexMip::cloneSolver() const {return new CplexMip(*this); }
 		  const char* CplexMip::_solverName() const { return "CplexMip"; }
 		  void CplexMip::_setColType(int i, CplexMip::ColTypes col_type) {
 		    // Note If a variable is to be changed to binary, a call to CPXchgbds
 		    // should also be made to change the bounds to 0 and 1.
 		    switch (col_type){
 		    case INTEGER: {
 		      const char t = 'I';
 		      CPXchgctype (cplexEnv(), _prob, 1, &i, &t);
 		    } break;
 		    case REAL: {
 		      const char t = 'C';
 		      CPXchgctype (cplexEnv(), _prob, 1, &i, &t);
 		    } break;
 		    default:
 		      break;
+		    }
+		  }
 		  CplexMip::ColTypes CplexMip::_getColType(int i) const {
 		    char t;
 		    CPXgetctype (cplexEnv(), _prob, &t, i, i);
 		    switch (t) {
 		    case 'I':
 		      return INTEGER;
 		    case 'C':
 		      return REAL;
 		    default:
 		      LEMON_ASSERT(false, "Invalid column type");
 		      return ColTypes();
+		    }
+		  }
 		  CplexMip::SolveExitStatus CplexMip::_solve() {
 		    int status;
 		    status = CPXmipopt (cplexEnv(), _prob);
 		    if (status==0)
 		      return SOLVED;
 		    else
 		      return UNSOLVED;
+		  }
 		  CplexMip::ProblemType CplexMip::_getType() const {
 		    int stat = CPXgetstat(cplexEnv(), _prob);
 		    //Fortunately, MIP statuses did not change for cplex 8.0
 		    switch (stat) {
 		    case CPXMIP_OPTIMAL:
 		      // Optimal integer solution has been found.
 		    case CPXMIP_OPTIMAL_TOL:
 		      // Optimal soluton with the tolerance defined by epgap or epagap has
 		      // been found.
 		      return OPTIMAL;
 		      //This also exists in later issues
 		      //    case CPXMIP_UNBOUNDED:
 		      //return UNBOUNDED;
 		      case CPXMIP_INFEASIBLE:
 		        return INFEASIBLE;
 		    default:
 		      return UNDEFINED;
+		    }
 		    //Unboundedness not treated well: the following is from cplex 9.0 doc
 		    // About Unboundedness
 		    // The treatment of models that are unbounded involves a few
 		    // subtleties. Specifically, a declaration of unboundedness means that
 		    // ILOG CPLEX has determined that the model has an unbounded
 		    // ray. Given any feasible solution x with objective z, a multiple of
 		    // the unbounded ray can be added to x to give a feasible solution
 		    // with objective z-1 (or z+1 for maximization models). Thus, if a
 		    // feasible solution exists, then the optimal objective is
 		    // unbounded. Note that ILOG CPLEX has not necessarily concluded that
 		    // a feasible solution exists. Users can call the routine CPXsolninfo
 		    // to determine whether ILOG CPLEX has also concluded that the model
 		    // has a feasible solution.
+		  }
 		  CplexMip::Value CplexMip::_getSol(int i) const {
 		    Value x;
 		    CPXgetmipx(cplexEnv(), _prob, &x, i, i);
 		    return x;
+		  }
 		  CplexMip::Value CplexMip::_getSolValue() const {
 		    Value objval;
 		    CPXgetmipobjval(cplexEnv(), _prob, &objval);
 		    return objval;
+		  }
 		} //namespace lemon

lemon/cplex.h

Show inline comments

 		/* -*- mode: C++; indent-tabs-mode: nil; -*-
+		 *
 		 * This file is a part of LEMON, a generic C++ optimization library.
+		 *
 		 * Copyright (C) 2003-2008
 		 * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
 		 * (Egervary Research Group on Combinatorial Optimization, EGRES).
+		 *
 		 * Permission to use, modify and distribute this software is granted
 		 * provided that this copyright notice appears in all copies. For
 		 * precise terms see the accompanying LICENSE file.
+		 *
 		 * This software is provided "AS IS" with no warranty of any kind,
 		 * express or implied, and with no claim as to its suitability for any
 		 * purpose.
+		 *
 		 */
 		#ifndef LEMON_CPLEX_H
 		#define LEMON_CPLEX_H
 		///\file
 		///\brief Header of the LEMON-CPLEX lp solver interface.
 		#include <lemon/lp_base.h>
 		struct cpxenv;
 		struct cpxlp;
 		namespace lemon {
 		  /// \brief Reference counted wrapper around cpxenv pointer
 		  ///
 		  /// The cplex uses environment object which is responsible for
 		  /// checking the proper license usage. This class provides a simple
 		  /// interface for share the environment object between different
 		  /// problems.
 		  class CplexEnv {
 		    friend class CplexBase;
 		  private:
 		    cpxenv* _env;
 		    mutable int* _cnt;
 		  public:
 		    /// \brief This exception is thrown when the license check is not
 		    /// sufficient
 		    class LicenseError : public Exception {
 		      friend class CplexEnv;
 		    private:
 		      LicenseError(int status);
 		      char _message[510];
 		    public:
 		      /// The short error message
 		      virtual const char* what() const throw() {
 		        return _message;
+		      }
 		    };
 		    /// Constructor
 		    CplexEnv();
 		    /// Shallow copy constructor
 		    CplexEnv(const CplexEnv&);
 		    /// Shallow assignement
 		    CplexEnv& operator=(const CplexEnv&);
 		    /// Destructor
 		    virtual ~CplexEnv();
 		  protected:
 		    cpxenv* cplexEnv() { return _env; }
 		    const cpxenv* cplexEnv() const { return _env; }
 		  };
 		  /// \brief Base interface for the CPLEX LP and MIP solver
 		  ///
 		  /// This class implements the common interface of the CPLEX LP and
 		  /// MIP solvers.
 		  /// \ingroup lp_group
 		  class CplexBase : virtual public LpBase {
 		  protected:
 		    CplexEnv _env;
 		    cpxlp* _prob;
 		    CplexBase();
 		    CplexBase(const CplexEnv&);
 		    CplexBase(const CplexBase &);
 		    virtual ~CplexBase();
 		    virtual int _addCol();
 		    virtual int _addRow();
 		    virtual void _eraseCol(int i);
 		    virtual void _eraseRow(int i);
 		    virtual void _eraseColId(int i);
 		    virtual void _eraseRowId(int i);
 		    virtual void _getColName(int col, std::string& name) const;
 		    virtual void _setColName(int col, const std::string& name);
 		    virtual int _colByName(const std::string& name) const;
 		    virtual void _getRowName(int row, std::string& name) const;
 		    virtual void _setRowName(int row, const std::string& name);
 		    virtual int _rowByName(const std::string& name) const;
 		    virtual void _setRowCoeffs(int i, ExprIterator b, ExprIterator e);
 		    virtual void _getRowCoeffs(int i, InsertIterator b) const;
 		    virtual void _setColCoeffs(int i, ExprIterator b, ExprIterator e);
 		    virtual void _getColCoeffs(int i, InsertIterator b) const;
 		    virtual void _setCoeff(int row, int col, Value value);
 		    virtual Value _getCoeff(int row, int col) const;
 		    virtual void _setColLowerBound(int i, Value value);
 		    virtual Value _getColLowerBound(int i) const;
 		    virtual void _setColUpperBound(int i, Value value);
 		    virtual Value _getColUpperBound(int i) const;
 		  private:
 		    void _set_row_bounds(int i, Value lb, Value ub);
 		  protected:
 		    virtual void _setRowLowerBound(int i, Value value);
 		    virtual Value _getRowLowerBound(int i) const;
 		    virtual void _setRowUpperBound(int i, Value value);
 		    virtual Value _getRowUpperBound(int i) const;
 		    virtual void _setObjCoeffs(ExprIterator b, ExprIterator e);
 		    virtual void _getObjCoeffs(InsertIterator b) const;
 		    virtual void _setObjCoeff(int i, Value obj_coef);
 		    virtual Value _getObjCoeff(int i) const;
 		    virtual void _setSense(Sense sense);
 		    virtual Sense _getSense() const;
 		    virtual void _clear();
 		  public:
 		    /// Returns the used \c CplexEnv instance
 		    const CplexEnv& env() const { return _env; }
 		    ///
 		    const cpxenv* cplexEnv() const { return _env.cplexEnv(); }
 		    cpxlp* cplexLp() { return _prob; }
 		    const cpxlp* cplexLp() const { return _prob; }
 		  };
 		  /// \brief Interface for the CPLEX LP solver
 		  ///
 		  /// This class implements an interface for the CPLEX LP solver.
 		  ///\ingroup lp_group
-		  class CplexLp : public CplexBase, public LpSolver {
+		  class CplexLp : public LpSolver, public CplexBase {
 		  public:
 		    /// \e
 		    CplexLp();
 		    /// \e
 		    CplexLp(const CplexEnv&);
 		    /// \e
 		    CplexLp(const CplexLp&);
 		    /// \e
 		    virtual ~CplexLp();
 		    /// \e
 		    virtual CplexLp* cloneSolver() const;
 		    /// \e
 		    virtual CplexLp* newSolver() const;
 		  private:
 		    // these values cannot retrieved element by element
 		    mutable std::vector<int> _col_status;
 		    mutable std::vector<int> _row_status;
 		    mutable std::vector<Value> _primal_ray;
 		    mutable std::vector<Value> _dual_ray;
 		    void _clear_temporals();
 		    SolveExitStatus convertStatus(int status);
 		  protected:
 		    virtual CplexLp* _cloneSolver() const;
 		    virtual CplexLp* _newSolver() const;
 		    virtual const char* _solverName() const;
 		    virtual SolveExitStatus _solve();
 		    virtual Value _getPrimal(int i) const;
 		    virtual Value _getDual(int i) const;
 		    virtual Value _getPrimalValue() const;
 		    virtual VarStatus _getColStatus(int i) const;
 		    virtual VarStatus _getRowStatus(int i) const;
 		    virtual Value _getPrimalRay(int i) const;
 		    virtual Value _getDualRay(int i) const;
 		    virtual ProblemType _getPrimalType() const;
 		    virtual ProblemType _getDualType() const;
 		  public:
 		    /// Solve with primal simplex method
 		    SolveExitStatus solvePrimal();
 		    /// Solve with dual simplex method
 		    SolveExitStatus solveDual();
 		    /// Solve with barrier method
 		    SolveExitStatus solveBarrier();
 		  };
 		  /// \brief Interface for the CPLEX MIP solver
 		  ///
 		  /// This class implements an interface for the CPLEX MIP solver.
 		  ///\ingroup lp_group
-		  class CplexMip : public CplexBase, public MipSolver {
+		  class CplexMip : public MipSolver, public CplexBase {
 		  public:
 		    /// \e
 		    CplexMip();
 		    /// \e
 		    CplexMip(const CplexEnv&);
 		    /// \e
 		    CplexMip(const CplexMip&);
 		    /// \e
 		    virtual ~CplexMip();
 		  protected:
 		    virtual CplexMip* _cloneSolver() const;
 		    virtual CplexMip* _newSolver() const;
 		    virtual const char* _solverName() const;
 		    virtual ColTypes _getColType(int col) const;
 		    virtual void _setColType(int col, ColTypes col_type);
 		    virtual SolveExitStatus _solve();
 		    virtual ProblemType _getType() const;
 		    virtual Value _getSol(int i) const;
 		    virtual Value _getSolValue() const;
 		  };
 		} //END OF NAMESPACE LEMON
 		#endif //LEMON_CPLEX_H

lemon/glpk.cc

Show inline comments

@@ -345,386 +345,386 @@
+		  }
 		  GlpkBase::Value GlpkBase::_getColUpperBound(int i) const {
 		    int b = glp_get_col_type(lp, i);
 		      switch (b) {
 		      case GLP_UP:
 		      case GLP_DB:
 		      case GLP_FX:
 		        return glp_get_col_ub(lp, i);
 		      default:
 		        return INF;
+		      }
+		  }
 		  void GlpkBase::_setRowLowerBound(int i, Value lo) {
 		    LEMON_ASSERT(lo != INF, "Invalid bound");
 		    int b = glp_get_row_type(lp, i);
 		    double up = glp_get_row_ub(lp, i);
 		    if (lo == -INF) {
 		      switch (b) {
 		      case GLP_FR:
 		      case GLP_LO:
 		        glp_set_row_bnds(lp, i, GLP_FR, lo, up);
 		        break;
 		      case GLP_UP:
 		        break;
 		      case GLP_DB:
 		      case GLP_FX:
 		        glp_set_row_bnds(lp, i, GLP_UP, lo, up);
 		        break;
 		      default:
 		        break;
+		      }
 		    } else {
 		      switch (b) {
 		      case GLP_FR:
 		      case GLP_LO:
 		        glp_set_row_bnds(lp, i, GLP_LO, lo, up);
 		        break;
 		      case GLP_UP:
 		      case GLP_DB:
 		      case GLP_FX:
 		        if (lo == up)
 		          glp_set_row_bnds(lp, i, GLP_FX, lo, up);
 		        else
 		          glp_set_row_bnds(lp, i, GLP_DB, lo, up);
 		        break;
 		      default:
 		        break;
+		      }
+		    }
+		  }
 		  GlpkBase::Value GlpkBase::_getRowLowerBound(int i) const {
 		    int b = glp_get_row_type(lp, i);
 		    switch (b) {
 		    case GLP_LO:
 		    case GLP_DB:
 		    case GLP_FX:
 		      return glp_get_row_lb(lp, i);
 		    default:
 		      return -INF;
+		    }
+		  }
 		  void GlpkBase::_setRowUpperBound(int i, Value up) {
 		    LEMON_ASSERT(up != -INF, "Invalid bound");
 		    int b = glp_get_row_type(lp, i);
 		    double lo = glp_get_row_lb(lp, i);
 		    if (up == INF) {
 		      switch (b) {
 		      case GLP_FR:
 		      case GLP_LO:
 		        break;
 		      case GLP_UP:
 		        glp_set_row_bnds(lp, i, GLP_FR, lo, up);
 		        break;
 		      case GLP_DB:
 		      case GLP_FX:
 		        glp_set_row_bnds(lp, i, GLP_LO, lo, up);
 		        break;
 		      default:
 		        break;
+		      }
 		    } else {
 		      switch (b) {
 		      case GLP_FR:
 		        glp_set_row_bnds(lp, i, GLP_UP, lo, up);
 		        break;
 		      case GLP_UP:
 		        glp_set_row_bnds(lp, i, GLP_UP, lo, up);
 		        break;
 		      case GLP_LO:
 		      case GLP_DB:
 		      case GLP_FX:
 		        if (lo == up)
 		          glp_set_row_bnds(lp, i, GLP_FX, lo, up);
 		        else
 		          glp_set_row_bnds(lp, i, GLP_DB, lo, up);
 		        break;
 		      default:
 		        break;
+		      }
+		    }
+		  }
 		  GlpkBase::Value GlpkBase::_getRowUpperBound(int i) const {
 		    int b = glp_get_row_type(lp, i);
 		    switch (b) {
 		    case GLP_UP:
 		    case GLP_DB:
 		    case GLP_FX:
 		      return glp_get_row_ub(lp, i);
 		    default:
 		      return INF;
+		    }
+		  }
 		  void GlpkBase::_setObjCoeffs(ExprIterator b, ExprIterator e) {
 		    for (int i = 1; i <= glp_get_num_cols(lp); ++i) {
 		      glp_set_obj_coef(lp, i, 0.0);
+		    }
 		    for (ExprIterator it = b; it != e; ++it) {
 		      glp_set_obj_coef(lp, it->first, it->second);
+		    }
+		  }
 		  void GlpkBase::_getObjCoeffs(InsertIterator b) const {
 		    for (int i = 1; i <= glp_get_num_cols(lp); ++i) {
 		      Value val = glp_get_obj_coef(lp, i);
 		      if (val != 0.0) {
 		        *b = std::make_pair(i, val);
 		        ++b;
+		      }
+		    }
+		  }
 		  void GlpkBase::_setObjCoeff(int i, Value obj_coef) {
 		    //i = 0 means the constant term (shift)
 		    glp_set_obj_coef(lp, i, obj_coef);
+		  }
 		  GlpkBase::Value GlpkBase::_getObjCoeff(int i) const {
 		    //i = 0 means the constant term (shift)
 		    return glp_get_obj_coef(lp, i);
+		  }
 		  void GlpkBase::_setSense(GlpkBase::Sense sense) {
 		    switch (sense) {
 		    case MIN:
 		      glp_set_obj_dir(lp, GLP_MIN);
 		      break;
 		    case MAX:
 		      glp_set_obj_dir(lp, GLP_MAX);
 		      break;
+		    }
+		  }
 		  GlpkBase::Sense GlpkBase::_getSense() const {
 		    switch(glp_get_obj_dir(lp)) {
 		    case GLP_MIN:
 		      return MIN;
 		    case GLP_MAX:
 		      return MAX;
 		    default:
 		      LEMON_ASSERT(false, "Wrong sense");
 		      return GlpkBase::Sense();
+		    }
+		  }
 		  void GlpkBase::_clear() {
 		    glp_erase_prob(lp);
 		    rows.clear();
 		    cols.clear();
+		  }
 		  // GlpkLp members
 		  GlpkLp::GlpkLp()
 		    : LpBase(), GlpkBase(), LpSolver() {
 		    messageLevel(MESSAGE_NO_OUTPUT);
+		  }
 		  GlpkLp::GlpkLp(const GlpkLp& other)
 		    : LpBase(other), GlpkBase(other), LpSolver(other) {
 		    messageLevel(MESSAGE_NO_OUTPUT);
+		  }
 		  GlpkLp* GlpkLp::_newSolver() const { return new GlpkLp; }
 		  GlpkLp* GlpkLp::_cloneSolver() const { return new GlpkLp(*this); }
 		  GlpkLp* GlpkLp::newSolver() const { return new GlpkLp; }
 		  GlpkLp* GlpkLp::cloneSolver() const { return new GlpkLp(*this); }
 		  const char* GlpkLp::_solverName() const { return "GlpkLp"; }
 		  void GlpkLp::_clear_temporals() {
 		    _primal_ray.clear();
 		    _dual_ray.clear();
+		  }
 		  GlpkLp::SolveExitStatus GlpkLp::_solve() {
 		    return solvePrimal();
+		  }
 		  GlpkLp::SolveExitStatus GlpkLp::solvePrimal() {
 		    _clear_temporals();
 		    glp_smcp smcp;
 		    glp_init_smcp(&smcp);
 		    switch (_message_level) {
 		    case MESSAGE_NO_OUTPUT:
 		      smcp.msg_lev = GLP_MSG_OFF;
 		      break;
 		    case MESSAGE_ERROR_MESSAGE:
 		      smcp.msg_lev = GLP_MSG_ERR;
 		      break;
 		    case MESSAGE_NORMAL_OUTPUT:
 		      smcp.msg_lev = GLP_MSG_ON;
 		      break;
 		    case MESSAGE_FULL_OUTPUT:
 		      smcp.msg_lev = GLP_MSG_ALL;
 		      break;
+		    }
 		    if (glp_simplex(lp, &smcp) != 0) return UNSOLVED;
 		    return SOLVED;
+		  }
 		  GlpkLp::SolveExitStatus GlpkLp::solveDual() {
 		    _clear_temporals();
 		    glp_smcp smcp;
 		    glp_init_smcp(&smcp);
 		    switch (_message_level) {
 		    case MESSAGE_NO_OUTPUT:
 		      smcp.msg_lev = GLP_MSG_OFF;
 		      break;
 		    case MESSAGE_ERROR_MESSAGE:
 		      smcp.msg_lev = GLP_MSG_ERR;
 		      break;
 		    case MESSAGE_NORMAL_OUTPUT:
 		      smcp.msg_lev = GLP_MSG_ON;
 		      break;
 		    case MESSAGE_FULL_OUTPUT:
 		      smcp.msg_lev = GLP_MSG_ALL;
 		      break;
+		    }
 		    smcp.meth = GLP_DUAL;
 		    if (glp_simplex(lp, &smcp) != 0) return UNSOLVED;
 		    return SOLVED;
+		  }
 		  GlpkLp::Value GlpkLp::_getPrimal(int i) const {
 		    return glp_get_col_prim(lp, i);
+		  }
 		  GlpkLp::Value GlpkLp::_getDual(int i) const {
 		    return glp_get_row_dual(lp, i);
+		  }
 		  GlpkLp::Value GlpkLp::_getPrimalValue() const {
 		    return glp_get_obj_val(lp);
+		  }
 		  GlpkLp::VarStatus GlpkLp::_getColStatus(int i) const {
 		    switch (glp_get_col_stat(lp, i)) {
 		    case GLP_BS:
 		      return BASIC;
 		    case GLP_UP:
 		      return UPPER;
 		    case GLP_LO:
 		      return LOWER;
 		    case GLP_NF:
 		      return FREE;
 		    case GLP_NS:
 		      return FIXED;
 		    default:
 		      LEMON_ASSERT(false, "Wrong column status");
 		      return GlpkLp::VarStatus();
+		    }
+		  }
 		  GlpkLp::VarStatus GlpkLp::_getRowStatus(int i) const {
 		    switch (glp_get_row_stat(lp, i)) {
 		    case GLP_BS:
 		      return BASIC;
 		    case GLP_UP:
 		      return UPPER;
 		    case GLP_LO:
 		      return LOWER;
 		    case GLP_NF:
 		      return FREE;
 		    case GLP_NS:
 		      return FIXED;
 		    default:
 		      LEMON_ASSERT(false, "Wrong row status");
 		      return GlpkLp::VarStatus();
+		    }
+		  }
 		  GlpkLp::Value GlpkLp::_getPrimalRay(int i) const {
 		    if (_primal_ray.empty()) {
 		      int row_num = glp_get_num_rows(lp);
 		      int col_num = glp_get_num_cols(lp);
 		      _primal_ray.resize(col_num + 1, 0.0);
 		      int index = glp_get_unbnd_ray(lp);
 		      if (index != 0) {
 		        // The primal ray is found in primal simplex second phase
 		        LEMON_ASSERT((index <= row_num ? glp_get_row_stat(lp, index) :
 		                      glp_get_col_stat(lp, index - row_num)) != GLP_BS,
 		                     "Wrong primal ray");
 		        bool negate = glp_get_obj_dir(lp) == GLP_MAX;
 		        if (index > row_num) {
 		          _primal_ray[index - row_num] = 1.0;
 		          if (glp_get_col_dual(lp, index - row_num) > 0) {
 		            negate = !negate;
+		          }
 		        } else {
 		          if (glp_get_row_dual(lp, index) > 0) {
 		            negate = !negate;
+		          }
+		        }
 		        std::vector<int> ray_indexes(row_num + 1);
 		        std::vector<Value> ray_values(row_num + 1);
 		        int ray_length = glp_eval_tab_col(lp, index, &ray_indexes.front(),
 		                                          &ray_values.front());
 		        for (int i = 1; i <= ray_length; ++i) {
 		          if (ray_indexes[i] > row_num) {
 		            _primal_ray[ray_indexes[i] - row_num] = ray_values[i];
+		          }
+		        }
 		        if (negate) {
 		          for (int i = 1; i <= col_num; ++i) {
 		            _primal_ray[i] = - _primal_ray[i];
+		          }
+		        }
 		      } else {
 		        for (int i = 1; i <= col_num; ++i) {
 		          _primal_ray[i] = glp_get_col_prim(lp, i);
+		        }
+		      }
+		    }
 		    return _primal_ray[i];
+		  }
 		  GlpkLp::Value GlpkLp::_getDualRay(int i) const {
 		    if (_dual_ray.empty()) {
 		      int row_num = glp_get_num_rows(lp);
 		      _dual_ray.resize(row_num + 1, 0.0);
 		      int index = glp_get_unbnd_ray(lp);
 		      if (index != 0) {
 		        // The dual ray is found in dual simplex second phase
 		        LEMON_ASSERT((index <= row_num ? glp_get_row_stat(lp, index) :
 		                      glp_get_col_stat(lp, index - row_num)) == GLP_BS,
 		                     "Wrong dual ray");
 		        int idx;
 		        bool negate = false;
 		        if (index > row_num) {
 		          idx = glp_get_col_bind(lp, index - row_num);
 		          if (glp_get_col_prim(lp, index - row_num) >
 		              glp_get_col_ub(lp, index - row_num)) {
 		            negate = true;
+		          }
 		        } else {
 		          idx = glp_get_row_bind(lp, index);
 		          if (glp_get_row_prim(lp, index) > glp_get_row_ub(lp, index)) {
 		            negate = true;
+		          }
+		        }
@@ -751,202 +751,202 @@
 		          } else {
 		            double res = glp_get_col_prim(lp, index - row_num);
 		            if (res > glp_get_col_ub(lp, index - row_num) + eps) {
 		              _dual_ray[i] = -1;
 		            } else if (res < glp_get_col_lb(lp, index - row_num) - eps) {
 		              _dual_ray[i] = 1;
 		            } else {
 		              _dual_ray[i] = 0;
+		            }
 		            _dual_ray[i] /= glp_get_sjj(lp, index - row_num);
+		          }
+		        }
 		        glp_btran(lp, &_dual_ray.front());
 		        for (int i = 1; i <= row_num; ++i) {
 		          _dual_ray[i] /= glp_get_rii(lp, i);
+		        }
+		      }
+		    }
 		    return _dual_ray[i];
+		  }
 		  GlpkLp::ProblemType GlpkLp::_getPrimalType() const {
 		    if (glp_get_status(lp) == GLP_OPT)
 		      return OPTIMAL;
 		    switch (glp_get_prim_stat(lp)) {
 		    case GLP_UNDEF:
 		      return UNDEFINED;
 		    case GLP_FEAS:
 		    case GLP_INFEAS:
 		      if (glp_get_dual_stat(lp) == GLP_NOFEAS) {
 		        return UNBOUNDED;
 		      } else {
 		        return UNDEFINED;
+		      }
 		    case GLP_NOFEAS:
 		      return INFEASIBLE;
 		    default:
 		      LEMON_ASSERT(false, "Wrong primal type");
 		      return  GlpkLp::ProblemType();
+		    }
+		  }
 		  GlpkLp::ProblemType GlpkLp::_getDualType() const {
 		    if (glp_get_status(lp) == GLP_OPT)
 		      return OPTIMAL;
 		    switch (glp_get_dual_stat(lp)) {
 		    case GLP_UNDEF:
 		      return UNDEFINED;
 		    case GLP_FEAS:
 		    case GLP_INFEAS:
 		      if (glp_get_prim_stat(lp) == GLP_NOFEAS) {
 		        return UNBOUNDED;
 		      } else {
 		        return UNDEFINED;
+		      }
 		    case GLP_NOFEAS:
 		      return INFEASIBLE;
 		    default:
 		      LEMON_ASSERT(false, "Wrong primal type");
 		      return  GlpkLp::ProblemType();
+		    }
+		  }
 		  void GlpkLp::presolver(bool b) {
 		    lpx_set_int_parm(lp, LPX_K_PRESOL, b ? 1 : 0);
+		  }
 		  void GlpkLp::messageLevel(MessageLevel m) {
 		    _message_level = m;
+		  }
 		  // GlpkMip members
 		  GlpkMip::GlpkMip()
 		    : LpBase(), GlpkBase(), MipSolver() {
 		    messageLevel(MESSAGE_NO_OUTPUT);
+		  }
 		  GlpkMip::GlpkMip(const GlpkMip& other)
 		    : LpBase(), GlpkBase(other), MipSolver() {
 		    messageLevel(MESSAGE_NO_OUTPUT);
+		  }
 		  void GlpkMip::_setColType(int i, GlpkMip::ColTypes col_type) {
 		    switch (col_type) {
 		    case INTEGER:
 		      glp_set_col_kind(lp, i, GLP_IV);
 		      break;
 		    case REAL:
 		      glp_set_col_kind(lp, i, GLP_CV);
 		      break;
+		    }
+		  }
 		  GlpkMip::ColTypes GlpkMip::_getColType(int i) const {
 		    switch (glp_get_col_kind(lp, i)) {
 		    case GLP_IV:
 		    case GLP_BV:
 		      return INTEGER;
 		    default:
 		      return REAL;
+		    }
+		  }
 		  GlpkMip::SolveExitStatus GlpkMip::_solve() {
 		    glp_smcp smcp;
 		    glp_init_smcp(&smcp);
 		    switch (_message_level) {
 		    case MESSAGE_NO_OUTPUT:
 		      smcp.msg_lev = GLP_MSG_OFF;
 		      break;
 		    case MESSAGE_ERROR_MESSAGE:
 		      smcp.msg_lev = GLP_MSG_ERR;
 		      break;
 		    case MESSAGE_NORMAL_OUTPUT:
 		      smcp.msg_lev = GLP_MSG_ON;
 		      break;
 		    case MESSAGE_FULL_OUTPUT:
 		      smcp.msg_lev = GLP_MSG_ALL;
 		      break;
+		    }
 		    smcp.meth = GLP_DUAL;
 		    if (glp_simplex(lp, &smcp) != 0) return UNSOLVED;
 		    if (glp_get_status(lp) != GLP_OPT) return SOLVED;
 		    glp_iocp iocp;
 		    glp_init_iocp(&iocp);
 		    switch (_message_level) {
 		    case MESSAGE_NO_OUTPUT:
 		      iocp.msg_lev = GLP_MSG_OFF;
 		      break;
 		    case MESSAGE_ERROR_MESSAGE:
 		      iocp.msg_lev = GLP_MSG_ERR;
 		      break;
 		    case MESSAGE_NORMAL_OUTPUT:
 		      iocp.msg_lev = GLP_MSG_ON;
 		      break;
 		    case MESSAGE_FULL_OUTPUT:
 		      iocp.msg_lev = GLP_MSG_ALL;
 		      break;
+		    }
 		    if (glp_intopt(lp, &iocp) != 0) return UNSOLVED;
 		    return SOLVED;
+		  }
 		  GlpkMip::ProblemType GlpkMip::_getType() const {
 		    switch (glp_get_status(lp)) {
 		    case GLP_OPT:
 		      switch (glp_mip_status(lp)) {
 		      case GLP_UNDEF:
 		        return UNDEFINED;
 		      case GLP_NOFEAS:
 		        return INFEASIBLE;
 		      case GLP_FEAS:
 		        return FEASIBLE;
 		      case GLP_OPT:
 		        return OPTIMAL;
 		      default:
 		        LEMON_ASSERT(false, "Wrong problem type.");
 		        return GlpkMip::ProblemType();
+		      }
 		    case GLP_NOFEAS:
 		      return INFEASIBLE;
 		    case GLP_INFEAS:
 		    case GLP_FEAS:
 		      if (glp_get_dual_stat(lp) == GLP_NOFEAS) {
 		        return UNBOUNDED;
 		      } else {
 		        return UNDEFINED;
+		      }
 		    default:
 		      LEMON_ASSERT(false, "Wrong problem type.");
 		      return GlpkMip::ProblemType();
+		    }
+		  }
 		  GlpkMip::Value GlpkMip::_getSol(int i) const {
 		    return glp_mip_col_val(lp, i);
+		  }
 		  GlpkMip::Value GlpkMip::_getSolValue() const {
 		    return glp_mip_obj_val(lp);
+		  }
 		  GlpkMip* GlpkMip::_newSolver() const { return new GlpkMip; }
 		  GlpkMip* GlpkMip::_cloneSolver() const {return new GlpkMip(*this); }
 		  GlpkMip* GlpkMip::newSolver() const { return new GlpkMip; }
 		  GlpkMip* GlpkMip::cloneSolver() const {return new GlpkMip(*this); }
 		  const char* GlpkMip::_solverName() const { return "GlpkMip"; }
 		  void GlpkMip::messageLevel(MessageLevel m) {
 		    _message_level = m;
+		  }
 		} //END OF NAMESPACE LEMON

lemon/glpk.h

Show inline comments

 		/* -*- mode: C++; indent-tabs-mode: nil; -*-
+		 *
 		 * This file is a part of LEMON, a generic C++ optimization library.
+		 *
 		 * Copyright (C) 2003-2008
 		 * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
 		 * (Egervary Research Group on Combinatorial Optimization, EGRES).
+		 *
 		 * Permission to use, modify and distribute this software is granted
 		 * provided that this copyright notice appears in all copies. For
 		 * precise terms see the accompanying LICENSE file.
+		 *
 		 * This software is provided "AS IS" with no warranty of any kind,
 		 * express or implied, and with no claim as to its suitability for any
 		 * purpose.
+		 *
 		 */
 		#ifndef LEMON_GLPK_H
 		#define LEMON_GLPK_H
 		///\file
 		///\brief Header of the LEMON-GLPK lp solver interface.
 		///\ingroup lp_group
 		#include <lemon/lp_base.h>
 		// forward declaration
 		#ifndef _GLP_PROB
 		#define _GLP_PROB
 		typedef struct { double _prob; } glp_prob;
 		/* LP/MIP problem object */
 		#endif
 		namespace lemon {
 		  /// \brief Base interface for the GLPK LP and MIP solver
 		  ///
 		  /// This class implements the common interface of the GLPK LP and MIP solver.
 		  /// \ingroup lp_group
 		  class GlpkBase : virtual public LpBase {
 		  protected:
 		    typedef glp_prob LPX;
 		    glp_prob* lp;
 		    GlpkBase();
 		    GlpkBase(const GlpkBase&);
 		    virtual ~GlpkBase();
 		  protected:
 		    virtual int _addCol();
 		    virtual int _addRow();
 		    virtual void _eraseCol(int i);
 		    virtual void _eraseRow(int i);
 		    virtual void _eraseColId(int i);
 		    virtual void _eraseRowId(int i);
 		    virtual void _getColName(int col, std::string& name) const;
 		    virtual void _setColName(int col, const std::string& name);
 		    virtual int _colByName(const std::string& name) const;
 		    virtual void _getRowName(int row, std::string& name) const;
 		    virtual void _setRowName(int row, const std::string& name);
 		    virtual int _rowByName(const std::string& name) const;
 		    virtual void _setRowCoeffs(int i, ExprIterator b, ExprIterator e);
 		    virtual void _getRowCoeffs(int i, InsertIterator b) const;
 		    virtual void _setColCoeffs(int i, ExprIterator b, ExprIterator e);
 		    virtual void _getColCoeffs(int i, InsertIterator b) const;
 		    virtual void _setCoeff(int row, int col, Value value);
 		    virtual Value _getCoeff(int row, int col) const;
 		    virtual void _setColLowerBound(int i, Value value);
 		    virtual Value _getColLowerBound(int i) const;
 		    virtual void _setColUpperBound(int i, Value value);
 		    virtual Value _getColUpperBound(int i) const;
 		    virtual void _setRowLowerBound(int i, Value value);
 		    virtual Value _getRowLowerBound(int i) const;
 		    virtual void _setRowUpperBound(int i, Value value);
 		    virtual Value _getRowUpperBound(int i) const;
 		    virtual void _setObjCoeffs(ExprIterator b, ExprIterator e);
 		    virtual void _getObjCoeffs(InsertIterator b) const;
 		    virtual void _setObjCoeff(int i, Value obj_coef);
 		    virtual Value _getObjCoeff(int i) const;
 		    virtual void _setSense(Sense);
 		    virtual Sense _getSense() const;
 		    virtual void _clear();
 		  public:
 		    ///Pointer to the underlying GLPK data structure.
 		    LPX *lpx() {return lp;}
 		    ///Const pointer to the underlying GLPK data structure.
 		    const LPX *lpx() const {return lp;}
 		    ///Returns the constraint identifier understood by GLPK.
 		    int lpxRow(Row r) const { return rows(id(r)); }
 		    ///Returns the variable identifier understood by GLPK.
 		    int lpxCol(Col c) const { return cols(id(c)); }
 		  };
 		  /// \brief Interface for the GLPK LP solver
 		  ///
 		  /// This class implements an interface for the GLPK LP solver.
 		  ///\ingroup lp_group
-		  class GlpkLp : public GlpkBase, public LpSolver {
+		  class GlpkLp : public LpSolver, public GlpkBase {
 		  public:
 		    ///\e
 		    GlpkLp();
 		    ///\e
 		    GlpkLp(const GlpkLp&);
 		    ///\e
 		    virtual GlpkLp* cloneSolver() const;
 		    ///\e
 		    virtual GlpkLp* newSolver() const;
 		  private:
 		    mutable std::vector<double> _primal_ray;
 		    mutable std::vector<double> _dual_ray;
 		    void _clear_temporals();
 		  protected:
 		    virtual GlpkLp* _cloneSolver() const;
 		    virtual GlpkLp* _newSolver() const;
 		    virtual const char* _solverName() const;
 		    virtual SolveExitStatus _solve();
 		    virtual Value _getPrimal(int i) const;
 		    virtual Value _getDual(int i) const;
 		    virtual Value _getPrimalValue() const;
 		    virtual VarStatus _getColStatus(int i) const;
 		    virtual VarStatus _getRowStatus(int i) const;
 		    virtual Value _getPrimalRay(int i) const;
 		    virtual Value _getDualRay(int i) const;
 		    ///\todo It should be clarified
 		    ///
 		    virtual ProblemType _getPrimalType() const;
 		    virtual ProblemType _getDualType() const;
 		  public:
 		    ///Solve with primal simplex
 		    SolveExitStatus solvePrimal();
 		    ///Solve with dual simplex
 		    SolveExitStatus solveDual();
 		    ///Turns on or off the presolver
 		    ///Turns on (\c b is \c true) or off (\c b is \c false) the presolver
 		    ///
 		    ///The presolver is off by default.
 		    void presolver(bool b);
 		    ///Enum for \c messageLevel() parameter
 		    enum MessageLevel {
 		      /// no output (default value)
 		      MESSAGE_NO_OUTPUT = 0,
 		      /// error messages only
 		      MESSAGE_ERROR_MESSAGE = 1,
 		      /// normal output
 		      MESSAGE_NORMAL_OUTPUT = 2,
 		      /// full output (includes informational messages)
 		      MESSAGE_FULL_OUTPUT = 3
 		    };
 		  private:
 		    MessageLevel _message_level;
 		  public:
 		    ///Set the verbosity of the messages
 		    ///Set the verbosity of the messages
 		    ///
 		    ///\param m is the level of the messages output by the solver routines.
 		    void messageLevel(MessageLevel m);
 		  };
 		  /// \brief Interface for the GLPK MIP solver
 		  ///
 		  /// This class implements an interface for the GLPK MIP solver.
 		  ///\ingroup lp_group
-		  class GlpkMip : public GlpkBase, public MipSolver {
+		  class GlpkMip : public MipSolver, public GlpkBase {
 		  public:
 		    ///\e
 		    GlpkMip();
 		    ///\e
 		    GlpkMip(const GlpkMip&);
 		    virtual GlpkMip* cloneSolver() const;
 		    virtual GlpkMip* newSolver() const;
 		  protected:
 		    virtual GlpkMip* _cloneSolver() const;
 		    virtual GlpkMip* _newSolver() const;
 		    virtual const char* _solverName() const;
 		    virtual ColTypes _getColType(int col) const;
 		    virtual void _setColType(int col, ColTypes col_type);
 		    virtual SolveExitStatus _solve();
 		    virtual ProblemType _getType() const;
 		    virtual Value _getSol(int i) const;
 		    virtual Value _getSolValue() const;
 		    ///Enum for \c messageLevel() parameter
 		    enum MessageLevel {
 		      /// no output (default value)
 		      MESSAGE_NO_OUTPUT = 0,
 		      /// error messages only
 		      MESSAGE_ERROR_MESSAGE = 1,
 		      /// normal output
 		      MESSAGE_NORMAL_OUTPUT = 2,
 		      /// full output (includes informational messages)
 		      MESSAGE_FULL_OUTPUT = 3
 		    };
 		  private:
 		    MessageLevel _message_level;
 		  public:
 		    ///Set the verbosity of the messages
 		    ///Set the verbosity of the messages
 		    ///
 		    ///\param m is the level of the messages output by the solver routines.
 		    void messageLevel(MessageLevel m);
 		  };
 		} //END OF NAMESPACE LEMON
 		#endif //LEMON_GLPK_H

lemon/lp_base.h

Show inline comments

@@ -729,458 +729,451 @@
 		      ///Multiply with a constant
 		      DualExpr &operator*=(const Value &v) {
 		        for (std::map<int, Value>::iterator it=comps.begin();
 		             it!=comps.end(); ++it)
 		          it->second*=v;
 		        return *this;
+		      }
 		      ///Division with a constant
 		      DualExpr &operator/=(const Value &v) {
 		        for (std::map<int, Value>::iterator it=comps.begin();
 		             it!=comps.end(); ++it)
 		          it->second/=v;
 		        return *this;
+		      }
 		      ///Iterator over the expression
 		      ///The iterator iterates over the terms of the expression.
 		      ///
 		      ///\code
 		      ///double s=0;
 		      ///for(LpBase::DualExpr::CoeffIt i(e);i!=INVALID;++i)
 		      ///  s+= *i * dual(i);
 		      ///\endcode
 		      class CoeffIt {
 		      private:
 		        std::map<int, Value>::iterator _it, _end;
 		      public:
 		        /// Sets the iterator to the first term
 		        /// Sets the iterator to the first term of the expression.
 		        ///
 		        CoeffIt(DualExpr& e)
 		          : _it(e.comps.begin()), _end(e.comps.end()){}
 		        /// Convert the iterator to the row of the term
 		        operator Row() const {
 		          return rowFromId(_it->first);
+		        }
 		        /// Returns the coefficient of the term
 		        Value& operator*() { return _it->second; }
 		        /// Returns the coefficient of the term
 		        const Value& operator*() const { return _it->second; }
 		        /// Next term
 		        /// Assign the iterator to the next term.
 		        ///
 		        CoeffIt& operator++() { ++_it; return *this; }
 		        /// Equality operator
 		        bool operator==(Invalid) const { return _it == _end; }
 		        /// Inequality operator
 		        bool operator!=(Invalid) const { return _it != _end; }
 		      };
 		      ///Iterator over the expression
 		      ///The iterator iterates over the terms of the expression.
 		      ///
 		      ///\code
 		      ///double s=0;
 		      ///for(LpBase::DualExpr::ConstCoeffIt i(e);i!=INVALID;++i)
 		      ///  s+= *i * dual(i);
 		      ///\endcode
 		      class ConstCoeffIt {
 		      private:
 		        std::map<int, Value>::const_iterator _it, _end;
 		      public:
 		        /// Sets the iterator to the first term
 		        /// Sets the iterator to the first term of the expression.
 		        ///
 		        ConstCoeffIt(const DualExpr& e)
 		          : _it(e.comps.begin()), _end(e.comps.end()){}
 		        /// Convert the iterator to the row of the term
 		        operator Row() const {
 		          return rowFromId(_it->first);
+		        }
 		        /// Returns the coefficient of the term
 		        const Value& operator*() const { return _it->second; }
 		        /// Next term
 		        /// Assign the iterator to the next term.
 		        ///
 		        ConstCoeffIt& operator++() { ++_it; return *this; }
 		        /// Equality operator
 		        bool operator==(Invalid) const { return _it == _end; }
 		        /// Inequality operator
 		        bool operator!=(Invalid) const { return _it != _end; }
 		      };
 		    };
 		  protected:
 		    class InsertIterator {
 		    private:
 		      std::map<int, Value>& _host;
 		      const _solver_bits::VarIndex& _index;
 		    public:
 		      typedef std::output_iterator_tag iterator_category;
 		      typedef void difference_type;
 		      typedef void value_type;
 		      typedef void reference;
 		      typedef void pointer;
 		      InsertIterator(std::map<int, Value>& host,
 		                   const _solver_bits::VarIndex& index)
 		        : _host(host), _index(index) {}
 		      InsertIterator& operator=(const std::pair<int, Value>& value) {
 		        typedef std::map<int, Value>::value_type pair_type;
 		        _host.insert(pair_type(_index[value.first], value.second));
 		        return *this;
+		      }
 		      InsertIterator& operator*() { return *this; }
 		      InsertIterator& operator++() { return *this; }
 		      InsertIterator operator++(int) { return *this; }
 		    };
 		    class ExprIterator {
 		    private:
 		      std::map<int, Value>::const_iterator _host_it;
 		      const _solver_bits::VarIndex& _index;
 		    public:
 		      typedef std::bidirectional_iterator_tag iterator_category;
 		      typedef std::ptrdiff_t difference_type;
 		      typedef const std::pair<int, Value> value_type;
 		      typedef value_type reference;
 		      class pointer {
 		      public:
 		        pointer(value_type& _value) : value(_value) {}
 		        value_type* operator->() { return &value; }
 		      private:
 		        value_type value;
 		      };
 		      ExprIterator(const std::map<int, Value>::const_iterator& host_it,
 		                   const _solver_bits::VarIndex& index)
 		        : _host_it(host_it), _index(index) {}
 		      reference operator*() {
 		        return std::make_pair(_index(_host_it->first), _host_it->second);
+		      }
 		      pointer operator->() {
 		        return pointer(operator*());
+		      }
 		      ExprIterator& operator++() { ++_host_it; return *this; }
 		      ExprIterator operator++(int) {
 		        ExprIterator tmp(*this); ++_host_it; return tmp;
+		      }
 		      ExprIterator& operator--() { --_host_it; return *this; }
 		      ExprIterator operator--(int) {
 		        ExprIterator tmp(*this); --_host_it; return tmp;
+		      }
 		      bool operator==(const ExprIterator& it) const {
 		        return _host_it == it._host_it;
+		      }
 		      bool operator!=(const ExprIterator& it) const {
 		        return _host_it != it._host_it;
+		      }
 		    };
 		  protected:
 		    //Abstract virtual functions
 		    virtual LpBase* _newSolver() const = 0;
 		    virtual LpBase* _cloneSolver() const = 0;
 		    virtual int _addColId(int col) { return cols.addIndex(col); }
 		    virtual int _addRowId(int row) { return rows.addIndex(row); }
 		    virtual void _eraseColId(int col) { cols.eraseIndex(col); }
 		    virtual void _eraseRowId(int row) { rows.eraseIndex(row); }
 		    virtual int _addCol() = 0;
 		    virtual int _addRow() = 0;
 		    virtual void _eraseCol(int col) = 0;
 		    virtual void _eraseRow(int row) = 0;
 		    virtual void _getColName(int col, std::string& name) const = 0;
 		    virtual void _setColName(int col, const std::string& name) = 0;
 		    virtual int _colByName(const std::string& name) const = 0;
 		    virtual void _getRowName(int row, std::string& name) const = 0;
 		    virtual void _setRowName(int row, const std::string& name) = 0;
 		    virtual int _rowByName(const std::string& name) const = 0;
 		    virtual void _setRowCoeffs(int i, ExprIterator b, ExprIterator e) = 0;
 		    virtual void _getRowCoeffs(int i, InsertIterator b) const = 0;
 		    virtual void _setColCoeffs(int i, ExprIterator b, ExprIterator e) = 0;
 		    virtual void _getColCoeffs(int i, InsertIterator b) const = 0;
 		    virtual void _setCoeff(int row, int col, Value value) = 0;
 		    virtual Value _getCoeff(int row, int col) const = 0;
 		    virtual void _setColLowerBound(int i, Value value) = 0;
 		    virtual Value _getColLowerBound(int i) const = 0;
 		    virtual void _setColUpperBound(int i, Value value) = 0;
 		    virtual Value _getColUpperBound(int i) const = 0;
 		    virtual void _setRowLowerBound(int i, Value value) = 0;
 		    virtual Value _getRowLowerBound(int i) const = 0;
 		    virtual void _setRowUpperBound(int i, Value value) = 0;
 		    virtual Value _getRowUpperBound(int i) const = 0;
 		    virtual void _setObjCoeffs(ExprIterator b, ExprIterator e) = 0;
 		    virtual void _getObjCoeffs(InsertIterator b) const = 0;
 		    virtual void _setObjCoeff(int i, Value obj_coef) = 0;
 		    virtual Value _getObjCoeff(int i) const = 0;
 		    virtual void _setSense(Sense) = 0;
 		    virtual Sense _getSense() const = 0;
 		    virtual void _clear() = 0;
 		    virtual const char* _solverName() const = 0;
 		    //Own protected stuff
 		    //Constant component of the objective function
 		    Value obj_const_comp;
 		    LpBase() : rows(), cols(), obj_const_comp(0) {}
 		  public:
 		    /// Virtual destructor
 		    virtual ~LpBase() {}
 		    ///Creates a new LP problem
 		    LpBase* newSolver() {return _newSolver();}
 		    ///Makes a copy of the LP problem
 		    LpBase* cloneSolver() {return _cloneSolver();}
 		    ///Gives back the name of the solver.
 		    const char* solverName() const {return _solverName();}
 		    ///\name Build up and modify the LP
 		    ///@{
 		    ///Add a new empty column (i.e a new variable) to the LP
 		    Col addCol() { Col c; c._id = _addColId(_addCol()); return c;}
 		    ///\brief Adds several new columns (i.e variables) at once
 		    ///
 		    ///This magic function takes a container as its argument and fills
 		    ///its elements with new columns (i.e. variables)
 		    ///\param t can be
 		    ///- a standard STL compatible iterable container with
 		    ///\ref Col as its \c values_type like
 		    ///\code
 		    ///std::vector<LpBase::Col>
 		    ///std::list<LpBase::Col>
 		    ///\endcode
 		    ///- a standard STL compatible iterable container with
 		    ///\ref Col as its \c mapped_type like
 		    ///\code
 		    ///std::map<AnyType,LpBase::Col>
 		    ///\endcode
 		    ///- an iterable lemon \ref concepts::WriteMap "write map" like
 		    ///\code
 		    ///ListGraph::NodeMap<LpBase::Col>
 		    ///ListGraph::ArcMap<LpBase::Col>
 		    ///\endcode
 		    ///\return The number of the created column.
 		#ifdef DOXYGEN
 		    template<class T>
 		    int addColSet(T &t) { return 0;}
 		#else
 		    template<class T>
 		    typename enable_if<typename T::value_type::LpCol,int>::type
 		    addColSet(T &t,dummy<0> = 0) {
 		      int s=0;
 		      for(typename T::iterator i=t.begin();i!=t.end();++i) {*i=addCol();s++;}
 		      return s;
+		    }
 		    template<class T>
 		    typename enable_if<typename T::value_type::second_type::LpCol,
 		                       int>::type
 		    addColSet(T &t,dummy<1> = 1) {
 		      int s=0;
 		      for(typename T::iterator i=t.begin();i!=t.end();++i) {
 		        i->second=addCol();
 		        s++;
+		      }
 		      return s;
+		    }
 		    template<class T>
 		    typename enable_if<typename T::MapIt::Value::LpCol,
 		                       int>::type
 		    addColSet(T &t,dummy<2> = 2) {
 		      int s=0;
 		      for(typename T::MapIt i(t); i!=INVALID; ++i)
+		        {
 		          i.set(addCol());
 		          s++;
+		        }
 		      return s;
+		    }
 		#endif
 		    ///Set a column (i.e a dual constraint) of the LP
 		    ///\param c is the column to be modified
 		    ///\param e is a dual linear expression (see \ref DualExpr)
 		    ///a better one.
 		    void col(Col c, const DualExpr &e) {
 		      e.simplify();
 		      _setColCoeffs(cols(id(c)), ExprIterator(e.comps.begin(), rows),
 		                    ExprIterator(e.comps.end(), rows));
+		    }
 		    ///Get a column (i.e a dual constraint) of the LP
 		    ///\param c is the column to get
 		    ///\return the dual expression associated to the column
 		    DualExpr col(Col c) const {
 		      DualExpr e;
 		      _getColCoeffs(cols(id(c)), InsertIterator(e.comps, rows));
 		      return e;
+		    }
 		    ///Add a new column to the LP
 		    ///\param e is a dual linear expression (see \ref DualExpr)
 		    ///\param o is the corresponding component of the objective
 		    ///function. It is 0 by default.
 		    ///\return The created column.
 		    Col addCol(const DualExpr &e, Value o = 0) {
 		      Col c=addCol();
 		      col(c,e);
 		      objCoeff(c,o);
 		      return c;
+		    }
 		    ///Add a new empty row (i.e a new constraint) to the LP
 		    ///This function adds a new empty row (i.e a new constraint) to the LP.
 		    ///\return The created row
 		    Row addRow() { Row r; r._id = _addRowId(_addRow()); return r;}
 		    ///\brief Add several new rows (i.e constraints) at once
 		    ///
 		    ///This magic function takes a container as its argument and fills
 		    ///its elements with new row (i.e. variables)
 		    ///\param t can be
 		    ///- a standard STL compatible iterable container with
 		    ///\ref Row as its \c values_type like
 		    ///\code
 		    ///std::vector<LpBase::Row>
 		    ///std::list<LpBase::Row>
 		    ///\endcode
 		    ///- a standard STL compatible iterable container with
 		    ///\ref Row as its \c mapped_type like
 		    ///\code
 		    ///std::map<AnyType,LpBase::Row>
 		    ///\endcode
 		    ///- an iterable lemon \ref concepts::WriteMap "write map" like
 		    ///\code
 		    ///ListGraph::NodeMap<LpBase::Row>
 		    ///ListGraph::ArcMap<LpBase::Row>
 		    ///\endcode
 		    ///\return The number of rows created.
 		#ifdef DOXYGEN
 		    template<class T>
 		    int addRowSet(T &t) { return 0;}
 		#else
 		    template<class T>
 		    typename enable_if<typename T::value_type::LpRow,int>::type
 		    addRowSet(T &t, dummy<0> = 0) {
 		      int s=0;
 		      for(typename T::iterator i=t.begin();i!=t.end();++i) {*i=addRow();s++;}
 		      return s;
+		    }
 		    template<class T>
 		    typename enable_if<typename T::value_type::second_type::LpRow, int>::type
 		    addRowSet(T &t, dummy<1> = 1) {
 		      int s=0;
 		      for(typename T::iterator i=t.begin();i!=t.end();++i) {
 		        i->second=addRow();
 		        s++;
+		      }
 		      return s;
+		    }
 		    template<class T>
 		    typename enable_if<typename T::MapIt::Value::LpRow, int>::type
 		    addRowSet(T &t, dummy<2> = 2) {
 		      int s=0;
 		      for(typename T::MapIt i(t); i!=INVALID; ++i)
+		        {
 		          i.set(addRow());
 		          s++;
+		        }
 		      return s;
+		    }
 		#endif
 		    ///Set a row (i.e a constraint) of the LP
 		    ///\param r is the row to be modified
 		    ///\param l is lower bound (-\ref INF means no bound)
 		    ///\param e is a linear expression (see \ref Expr)
 		    ///\param u is the upper bound (\ref INF means no bound)
 		    void row(Row r, Value l, const Expr &e, Value u) {
 		      e.simplify();
 		      _setRowCoeffs(rows(id(r)), ExprIterator(e.comps.begin(), cols),
 		                    ExprIterator(e.comps.end(), cols));
 		      _setRowLowerBound(rows(id(r)),l - *e);
 		      _setRowUpperBound(rows(id(r)),u - *e);
+		    }
 		    ///Set a row (i.e a constraint) of the LP
 		    ///\param r is the row to be modified
 		    ///\param c is a linear expression (see \ref Constr)
 		    void row(Row r, const Constr &c) {
 		      row(r, c.lowerBounded()?c.lowerBound():-INF,
 		          c.expr(), c.upperBounded()?c.upperBound():INF);
+		    }
 		    ///Get a row (i.e a constraint) of the LP
 		    ///\param r is the row to get
 		    ///\return the expression associated to the row
@@ -1632,449 +1625,445 @@
+		  }
 		  ///Create constraint
 		  ///\relates LpBase::Constr
 		  ///
 		  inline LpBase::Constr operator>=(const LpBase::Expr &e,
 		                                   const LpBase::Value &f) {
 		    return LpBase::Constr(f, e, LpBase::INF);
+		  }
 		  ///Create constraint
 		  ///\relates LpBase::Constr
 		  ///
 		  inline LpBase::Constr operator==(const LpBase::Expr &e,
 		                                   const LpBase::Value &f) {
 		    return LpBase::Constr(f, e, f);
+		  }
 		  ///Create constraint
 		  ///\relates LpBase::Constr
 		  ///
 		  inline LpBase::Constr operator==(const LpBase::Expr &e,
 		                                   const LpBase::Expr &f) {
 		    return LpBase::Constr(0, f - e, 0);
+		  }
 		  ///Create constraint
 		  ///\relates LpBase::Constr
 		  ///
 		  inline LpBase::Constr operator<=(const LpBase::Value &n,
 		                                   const LpBase::Constr &c) {
 		    LpBase::Constr tmp(c);
 		    LEMON_ASSERT(isNaN(tmp.lowerBound()), "Wrong LP constraint");
 		    tmp.lowerBound()=n;
 		    return tmp;
+		  }
 		  ///Create constraint
 		  ///\relates LpBase::Constr
 		  ///
 		  inline LpBase::Constr operator<=(const LpBase::Constr &c,
 		                                   const LpBase::Value &n)
+		  {
 		    LpBase::Constr tmp(c);
 		    LEMON_ASSERT(isNaN(tmp.upperBound()), "Wrong LP constraint");
 		    tmp.upperBound()=n;
 		    return tmp;
+		  }
 		  ///Create constraint
 		  ///\relates LpBase::Constr
 		  ///
 		  inline LpBase::Constr operator>=(const LpBase::Value &n,
 		                                   const LpBase::Constr &c) {
 		    LpBase::Constr tmp(c);
 		    LEMON_ASSERT(isNaN(tmp.upperBound()), "Wrong LP constraint");
 		    tmp.upperBound()=n;
 		    return tmp;
+		  }
 		  ///Create constraint
 		  ///\relates LpBase::Constr
 		  ///
 		  inline LpBase::Constr operator>=(const LpBase::Constr &c,
 		                                   const LpBase::Value &n)
+		  {
 		    LpBase::Constr tmp(c);
 		    LEMON_ASSERT(isNaN(tmp.lowerBound()), "Wrong LP constraint");
 		    tmp.lowerBound()=n;
 		    return tmp;
+		  }
 		  ///Addition
 		  ///\relates LpBase::DualExpr
 		  ///
 		  inline LpBase::DualExpr operator+(const LpBase::DualExpr &a,
 		                                    const LpBase::DualExpr &b) {
 		    LpBase::DualExpr tmp(a);
 		    tmp+=b;
 		    return tmp;
+		  }
 		  ///Substraction
 		  ///\relates LpBase::DualExpr
 		  ///
 		  inline LpBase::DualExpr operator-(const LpBase::DualExpr &a,
 		                                    const LpBase::DualExpr &b) {
 		    LpBase::DualExpr tmp(a);
 		    tmp-=b;
 		    return tmp;
+		  }
 		  ///Multiply with constant
 		  ///\relates LpBase::DualExpr
 		  ///
 		  inline LpBase::DualExpr operator*(const LpBase::DualExpr &a,
 		                                    const LpBase::Value &b) {
 		    LpBase::DualExpr tmp(a);
 		    tmp*=b;
 		    return tmp;
+		  }
 		  ///Multiply with constant
 		  ///\relates LpBase::DualExpr
 		  ///
 		  inline LpBase::DualExpr operator*(const LpBase::Value &a,
 		                                    const LpBase::DualExpr &b) {
 		    LpBase::DualExpr tmp(b);
 		    tmp*=a;
 		    return tmp;
+		  }
 		  ///Divide with constant
 		  ///\relates LpBase::DualExpr
 		  ///
 		  inline LpBase::DualExpr operator/(const LpBase::DualExpr &a,
 		                                    const LpBase::Value &b) {
 		    LpBase::DualExpr tmp(a);
 		    tmp/=b;
 		    return tmp;
+		  }
 		  /// \ingroup lp_group
 		  ///
 		  /// \brief Common base class for LP solvers
 		  ///
 		  /// This class is an abstract base class for LP solvers. This class
 		  /// provides a full interface for set and modify an LP problem,
 		  /// solve it and retrieve the solution. You can use one of the
 		  /// descendants as a concrete implementation, or the \c Lp
 		  /// default LP solver. However, if you would like to handle LP
 		  /// solvers as reference or pointer in a generic way, you can use
 		  /// this class directly.
 		  class LpSolver : virtual public LpBase {
 		  public:
 		    /// The problem types for primal and dual problems
 		    enum ProblemType {
 		      ///Feasible solution hasn't been found (but may exist).
 		      UNDEFINED = 0,
 		      ///The problem has no feasible solution
 		      INFEASIBLE = 1,
 		      ///Feasible solution found
 		      FEASIBLE = 2,
 		      ///Optimal solution exists and found
 		      OPTIMAL = 3,
 		      ///The cost function is unbounded
 		      UNBOUNDED = 4
 		    };
 		    ///The basis status of variables
 		    enum VarStatus {
 		      /// The variable is in the basis
 		      BASIC,
 		      /// The variable is free, but not basic
 		      FREE,
 		      /// The variable has active lower bound
 		      LOWER,
 		      /// The variable has active upper bound
 		      UPPER,
 		      /// The variable is non-basic and fixed
 		      FIXED
 		    };
 		  protected:
 		    virtual SolveExitStatus _solve() = 0;
 		    virtual Value _getPrimal(int i) const = 0;
 		    virtual Value _getDual(int i) const = 0;
 		    virtual Value _getPrimalRay(int i) const = 0;
 		    virtual Value _getDualRay(int i) const = 0;
 		    virtual Value _getPrimalValue() const = 0;
 		    virtual VarStatus _getColStatus(int i) const = 0;
 		    virtual VarStatus _getRowStatus(int i) const = 0;
 		    virtual ProblemType _getPrimalType() const = 0;
 		    virtual ProblemType _getDualType() const = 0;
 		  public:
 		    ///Allocate a new LP problem instance
 		    virtual LpSolver* newSolver() const = 0;
 		    ///Make a copy of the LP problem
 		    virtual LpSolver* cloneSolver() const = 0;
 		    ///\name Solve the LP
 		    ///@{
 		    ///\e Solve the LP problem at hand
 		    ///
 		    ///\return The result of the optimization procedure. Possible
 		    ///values and their meanings can be found in the documentation of
 		    ///\ref SolveExitStatus.
 		    SolveExitStatus solve() { return _solve(); }
 		    ///@}
 		    ///\name Obtain the solution
 		    ///@{
 		    /// The type of the primal problem
 		    ProblemType primalType() const {
 		      return _getPrimalType();
+		    }
 		    /// The type of the dual problem
 		    ProblemType dualType() const {
 		      return _getDualType();
+		    }
 		    /// Return the primal value of the column
 		    /// Return the primal value of the column.
 		    /// \pre The problem is solved.
 		    Value primal(Col c) const { return _getPrimal(cols(id(c))); }
 		    /// Return the primal value of the expression
 		    /// Return the primal value of the expression, i.e. the dot
 		    /// product of the primal solution and the expression.
 		    /// \pre The problem is solved.
 		    Value primal(const Expr& e) const {
 		      double res = *e;
 		      for (Expr::ConstCoeffIt c(e); c != INVALID; ++c) {
 		        res += *c * primal(c);
+		      }
 		      return res;
+		    }
 		    /// Returns a component of the primal ray
 		    /// The primal ray is solution of the modified primal problem,
 		    /// where we change each finite bound to 0, and we looking for a
 		    /// negative objective value in case of minimization, and positive
 		    /// objective value for maximization. If there is such solution,
 		    /// that proofs the unsolvability of the dual problem, and if a
 		    /// feasible primal solution exists, then the unboundness of
 		    /// primal problem.
 		    ///
 		    /// \pre The problem is solved and the dual problem is infeasible.
 		    /// \note Some solvers does not provide primal ray calculation
 		    /// functions.
 		    Value primalRay(Col c) const { return _getPrimalRay(cols(id(c))); }
 		    /// Return the dual value of the row
 		    /// Return the dual value of the row.
 		    /// \pre The problem is solved.
 		    Value dual(Row r) const { return _getDual(rows(id(r))); }
 		    /// Return the dual value of the dual expression
 		    /// Return the dual value of the dual expression, i.e. the dot
 		    /// product of the dual solution and the dual expression.
 		    /// \pre The problem is solved.
 		    Value dual(const DualExpr& e) const {
 		      double res = 0.0;
 		      for (DualExpr::ConstCoeffIt r(e); r != INVALID; ++r) {
 		        res += *r * dual(r);
+		      }
 		      return res;
+		    }
 		    /// Returns a component of the dual ray
 		    /// The dual ray is solution of the modified primal problem, where
 		    /// we change each finite bound to 0 (i.e. the objective function
 		    /// coefficients in the primal problem), and we looking for a
 		    /// ositive objective value. If there is such solution, that
 		    /// proofs the unsolvability of the primal problem, and if a
 		    /// feasible dual solution exists, then the unboundness of
 		    /// dual problem.
 		    ///
 		    /// \pre The problem is solved and the primal problem is infeasible.
 		    /// \note Some solvers does not provide dual ray calculation
 		    /// functions.
 		    Value dualRay(Row r) const { return _getDualRay(rows(id(r))); }
 		    /// Return the basis status of the column
 		    /// \see VarStatus
 		    VarStatus colStatus(Col c) const { return _getColStatus(cols(id(c))); }
 		    /// Return the basis status of the row
 		    /// \see VarStatus
 		    VarStatus rowStatus(Row r) const { return _getRowStatus(rows(id(r))); }
 		    ///The value of the objective function
 		    ///\return
 		    ///- \ref INF or -\ref INF means either infeasibility or unboundedness
 		    /// of the primal problem, depending on whether we minimize or maximize.
 		    ///- \ref NaN if no primal solution is found.
 		    ///- The (finite) objective value if an optimal solution is found.
 		    Value primal() const { return _getPrimalValue()+obj_const_comp;}
 		    ///@}
 		    LpSolver* newSolver() {return _newSolver();}
 		    LpSolver* cloneSolver() {return _cloneSolver();}
 		  protected:
 		    virtual LpSolver* _newSolver() const = 0;
 		    virtual LpSolver* _cloneSolver() const = 0;
 		  };
 		  /// \ingroup lp_group
 		  ///
 		  /// \brief Common base class for MIP solvers
 		  ///
 		  /// This class is an abstract base class for MIP solvers. This class
 		  /// provides a full interface for set and modify an MIP problem,
 		  /// solve it and retrieve the solution. You can use one of the
 		  /// descendants as a concrete implementation, or the \c Lp
 		  /// default MIP solver. However, if you would like to handle MIP
 		  /// solvers as reference or pointer in a generic way, you can use
 		  /// this class directly.
 		  class MipSolver : virtual public LpBase {
 		  public:
 		    /// The problem types for MIP problems
 		    enum ProblemType {
 		      ///Feasible solution hasn't been found (but may exist).
 		      UNDEFINED = 0,
 		      ///The problem has no feasible solution
 		      INFEASIBLE = 1,
 		      ///Feasible solution found
 		      FEASIBLE = 2,
 		      ///Optimal solution exists and found
 		      OPTIMAL = 3,
 		      ///The cost function is unbounded
 		      ///
 		      ///The Mip or at least the relaxed problem is unbounded
 		      UNBOUNDED = 4
 		    };
 		    ///Allocate a new MIP problem instance
 		    virtual MipSolver* newSolver() const = 0;
 		    ///Make a copy of the MIP problem
 		    virtual MipSolver* cloneSolver() const = 0;
 		    ///\name Solve the MIP
 		    ///@{
 		    /// Solve the MIP problem at hand
 		    ///
 		    ///\return The result of the optimization procedure. Possible
 		    ///values and their meanings can be found in the documentation of
 		    ///\ref SolveExitStatus.
 		    SolveExitStatus solve() { return _solve(); }
 		    ///@}
 		    ///\name Setting column type
 		    ///@{
 		    ///Possible variable (column) types (e.g. real, integer, binary etc.)
 		    enum ColTypes {
 		      ///Continuous variable (default)
 		      REAL = 0,
 		      ///Integer variable
 		      INTEGER = 1
 		    };
 		    ///Sets the type of the given column to the given type
 		    ///Sets the type of the given column to the given type.
 		    ///
 		    void colType(Col c, ColTypes col_type) {
 		      _setColType(cols(id(c)),col_type);
+		    }
 		    ///Gives back the type of the column.
 		    ///Gives back the type of the column.
 		    ///
 		    ColTypes colType(Col c) const {
 		      return _getColType(cols(id(c)));
+		    }
 		    ///@}
 		    ///\name Obtain the solution
 		    ///@{
 		    /// The type of the MIP problem
 		    ProblemType type() const {
 		      return _getType();
+		    }
 		    /// Return the value of the row in the solution
 		    ///  Return the value of the row in the solution.
 		    /// \pre The problem is solved.
 		    Value sol(Col c) const { return _getSol(cols(id(c))); }
 		    /// Return the value of the expression in the solution
 		    /// Return the value of the expression in the solution, i.e. the
 		    /// dot product of the solution and the expression.
 		    /// \pre The problem is solved.
 		    Value sol(const Expr& e) const {
 		      double res = *e;
 		      for (Expr::ConstCoeffIt c(e); c != INVALID; ++c) {
 		        res += *c * sol(c);
+		      }
 		      return res;
+		    }
 		    ///The value of the objective function
 		    ///\return
 		    ///- \ref INF or -\ref INF means either infeasibility or unboundedness
 		    /// of the problem, depending on whether we minimize or maximize.
 		    ///- \ref NaN if no primal solution is found.
 		    ///- The (finite) objective value if an optimal solution is found.
 		    Value solValue() const { return _getSolValue()+obj_const_comp;}
 		    ///@}
 		  protected:
 		    virtual SolveExitStatus _solve() = 0;
 		    virtual ColTypes _getColType(int col) const = 0;
 		    virtual void _setColType(int col, ColTypes col_type) = 0;
 		    virtual ProblemType _getType() const = 0;
 		    virtual Value _getSol(int i) const = 0;
 		    virtual Value _getSolValue() const = 0;
 		  public:
 		    MipSolver* newSolver() {return _newSolver();}
 		    MipSolver* cloneSolver() {return _cloneSolver();}
 		  protected:
 		    virtual MipSolver* _newSolver() const = 0;
 		    virtual MipSolver* _cloneSolver() const = 0;
 		  };
 		} //namespace lemon
 		#endif //LEMON_LP_BASE_H

lemon/lp_skeleton.cc

Show inline comments

 		/* -*- mode: C++; indent-tabs-mode: nil; -*-
+		 *
 		 * This file is a part of LEMON, a generic C++ optimization library.
+		 *
 		 * Copyright (C) 2003-2008
 		 * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
 		 * (Egervary Research Group on Combinatorial Optimization, EGRES).
+		 *
 		 * Permission to use, modify and distribute this software is granted
 		 * provided that this copyright notice appears in all copies. For
 		 * precise terms see the accompanying LICENSE file.
+		 *
 		 * This software is provided "AS IS" with no warranty of any kind,
 		 * express or implied, and with no claim as to its suitability for any
 		 * purpose.
+		 *
 		 */
 		#include <lemon/lp_skeleton.h>
 		///\file
 		///\brief A skeleton file to implement LP solver interfaces
 		namespace lemon {
 		  int SkeletonSolverBase::_addCol()
+		  {
 		    return ++col_num;
+		  }
 		  int SkeletonSolverBase::_addRow()
+		  {
 		    return ++row_num;
+		  }
 		  void SkeletonSolverBase::_eraseCol(int) {}
 		  void SkeletonSolverBase::_eraseRow(int) {}
 		  void SkeletonSolverBase::_getColName(int, std::string &) const {}
 		  void SkeletonSolverBase::_setColName(int, const std::string &) {}
 		  int SkeletonSolverBase::_colByName(const std::string&) const { return -1; }
 		  void SkeletonSolverBase::_getRowName(int, std::string &) const {}
 		  void SkeletonSolverBase::_setRowName(int, const std::string &) {}
 		  int SkeletonSolverBase::_rowByName(const std::string&) const { return -1; }
 		  void SkeletonSolverBase::_setRowCoeffs(int, ExprIterator, ExprIterator) {}
 		  void SkeletonSolverBase::_getRowCoeffs(int, InsertIterator) const {}
 		  void SkeletonSolverBase::_setColCoeffs(int, ExprIterator, ExprIterator) {}
 		  void SkeletonSolverBase::_getColCoeffs(int, InsertIterator) const {}
 		  void SkeletonSolverBase::_setCoeff(int, int, Value) {}
 		  SkeletonSolverBase::Value SkeletonSolverBase::_getCoeff(int, int) const
 		  { return 0; }
 		  void SkeletonSolverBase::_setColLowerBound(int, Value) {}
 		  SkeletonSolverBase::Value SkeletonSolverBase::_getColLowerBound(int) const
 		  {  return 0; }
 		  void SkeletonSolverBase::_setColUpperBound(int, Value) {}
 		  SkeletonSolverBase::Value SkeletonSolverBase::_getColUpperBound(int) const
 		  {  return 0; }
 		  void SkeletonSolverBase::_setRowLowerBound(int, Value) {}
 		  SkeletonSolverBase::Value SkeletonSolverBase::_getRowLowerBound(int) const
 		  {  return 0; }
 		  void SkeletonSolverBase::_setRowUpperBound(int, Value) {}
 		  SkeletonSolverBase::Value SkeletonSolverBase::_getRowUpperBound(int) const
 		  {  return 0; }
 		  void SkeletonSolverBase::_setObjCoeffs(ExprIterator, ExprIterator) {}
 		  void SkeletonSolverBase::_getObjCoeffs(InsertIterator) const {};
 		  void SkeletonSolverBase::_setObjCoeff(int, Value) {}
 		  SkeletonSolverBase::Value SkeletonSolverBase::_getObjCoeff(int) const
 		  {  return 0; }
 		  void SkeletonSolverBase::_setSense(Sense) {}
 		  SkeletonSolverBase::Sense SkeletonSolverBase::_getSense() const
 		  { return MIN; }
 		  void SkeletonSolverBase::_clear() {
 		    row_num = col_num = 0;
+		  }
 		  LpSkeleton::SolveExitStatus LpSkeleton::_solve() { return SOLVED; }
 		  LpSkeleton::Value LpSkeleton::_getPrimal(int) const { return 0; }
 		  LpSkeleton::Value LpSkeleton::_getDual(int) const { return 0; }
 		  LpSkeleton::Value LpSkeleton::_getPrimalValue() const { return 0; }
 		  LpSkeleton::Value LpSkeleton::_getPrimalRay(int) const { return 0; }
 		  LpSkeleton::Value LpSkeleton::_getDualRay(int) const { return 0; }
 		  LpSkeleton::ProblemType LpSkeleton::_getPrimalType() const
 		  { return UNDEFINED; }
 		  LpSkeleton::ProblemType LpSkeleton::_getDualType() const
 		  { return UNDEFINED; }
 		  LpSkeleton::VarStatus LpSkeleton::_getColStatus(int) const
 		  { return BASIC; }
 		  LpSkeleton::VarStatus LpSkeleton::_getRowStatus(int) const
 		  { return BASIC; }
-		  LpSkeleton* LpSkeleton::_newSolver() const
+		  LpSkeleton* LpSkeleton::newSolver() const
 		  { return static_cast<LpSkeleton*>(0); }
-		  LpSkeleton* LpSkeleton::_cloneSolver() const
+		  LpSkeleton* LpSkeleton::cloneSolver() const
 		  { return static_cast<LpSkeleton*>(0); }
 		  const char* LpSkeleton::_solverName() const { return "LpSkeleton"; }
 		  MipSkeleton::SolveExitStatus MipSkeleton::_solve()
 		  { return SOLVED; }
 		  MipSkeleton::Value MipSkeleton::_getSol(int) const { return 0; }
 		  MipSkeleton::Value MipSkeleton::_getSolValue() const { return 0; }
 		  MipSkeleton::ProblemType MipSkeleton::_getType() const
 		  { return UNDEFINED; }
-		  MipSkeleton* MipSkeleton::_newSolver() const
+		  MipSkeleton* MipSkeleton::newSolver() const
 		  { return static_cast<MipSkeleton*>(0); }
-		  MipSkeleton* MipSkeleton::_cloneSolver() const
+		  MipSkeleton* MipSkeleton::cloneSolver() const
 		  { return static_cast<MipSkeleton*>(0); }
 		  const char* MipSkeleton::_solverName() const { return "MipSkeleton"; }
 		} //namespace lemon

lemon/lp_skeleton.h

Show inline comments

 		/* -*- mode: C++; indent-tabs-mode: nil; -*-
+		 *
 		 * This file is a part of LEMON, a generic C++ optimization library.
+		 *
 		 * Copyright (C) 2003-2008
 		 * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
 		 * (Egervary Research Group on Combinatorial Optimization, EGRES).
+		 *
 		 * Permission to use, modify and distribute this software is granted
 		 * provided that this copyright notice appears in all copies. For
 		 * precise terms see the accompanying LICENSE file.
+		 *
 		 * This software is provided "AS IS" with no warranty of any kind,
 		 * express or implied, and with no claim as to its suitability for any
 		 * purpose.
+		 *
 		 */
 		#ifndef LEMON_LP_SKELETON_H
 		#define LEMON_LP_SKELETON_H
 		#include <lemon/lp_base.h>
 		///\file
-		///\brief A skeleton file to implement LP solver interfaces
+		///\brief Skeleton file to implement LP/MIP solver interfaces
 		///
 		///The classes in this file do nothing, but they can serve as skeletons when
 		///implementing an interface to new solvers.
 		namespace lemon {
-		  ///A skeleton class to implement LP solver interfaces
+		  ///A skeleton class to implement LP/MIP solver base interface
 		  ///This class does nothing, but it can serve as a skeleton when
 		  ///implementing an interface to new solvers.
 		  class SkeletonSolverBase : public virtual LpBase {
 		    int col_num,row_num;
 		  protected:
 		    SkeletonSolverBase()
 		      : col_num(-1), row_num(-1) {}
 		    /// \e
 		    virtual int _addCol();
 		    /// \e
 		    virtual int _addRow();
 		    /// \e
 		    virtual void _eraseCol(int i);
 		    /// \e
 		    virtual void _eraseRow(int i);
 		    /// \e
 		    virtual void _getColName(int col, std::string& name) const;
 		    /// \e
 		    virtual void _setColName(int col, const std::string& name);
 		    /// \e
 		    virtual int _colByName(const std::string& name) const;
 		    /// \e
 		    virtual void _getRowName(int row, std::string& name) const;
 		    /// \e
 		    virtual void _setRowName(int row, const std::string& name);
 		    /// \e
 		    virtual int _rowByName(const std::string& name) const;
 		    /// \e
 		    virtual void _setRowCoeffs(int i, ExprIterator b, ExprIterator e);
 		    /// \e
 		    virtual void _getRowCoeffs(int i, InsertIterator b) const;
 		    /// \e
 		    virtual void _setColCoeffs(int i, ExprIterator b, ExprIterator e);
 		    /// \e
 		    virtual void _getColCoeffs(int i, InsertIterator b) const;
 		    /// Set one element of the coefficient matrix
 		    virtual void _setCoeff(int row, int col, Value value);
 		    /// Get one element of the coefficient matrix
 		    virtual Value _getCoeff(int row, int col) const;
 		    /// The lower bound of a variable (column) have to be given by an
 		    /// extended number of type Value, i.e. a finite number of type
 		    /// Value or -\ref INF.
 		    virtual void _setColLowerBound(int i, Value value);
 		    /// \e
 		    /// The lower bound of a variable (column) is an
 		    /// extended number of type Value, i.e. a finite number of type
 		    /// Value or -\ref INF.
 		    virtual Value _getColLowerBound(int i) const;
 		    /// The upper bound of a variable (column) have to be given by an
 		    /// extended number of type Value, i.e. a finite number of type
 		    /// Value or \ref INF.
 		    virtual void _setColUpperBound(int i, Value value);
 		    /// \e
 		    /// The upper bound of a variable (column) is an
 		    /// extended number of type Value, i.e. a finite number of type
 		    /// Value or \ref INF.
 		    virtual Value _getColUpperBound(int i) const;
 		    /// The lower bound of a constraint (row) have to be given by an
 		    /// extended number of type Value, i.e. a finite number of type
 		    /// Value or -\ref INF.
 		    virtual void _setRowLowerBound(int i, Value value);
 		    /// \e
 		    /// The lower bound of a constraint (row) is an
 		    /// extended number of type Value, i.e. a finite number of type
 		    /// Value or -\ref INF.
 		    virtual Value _getRowLowerBound(int i) const;
 		    /// The upper bound of a constraint (row) have to be given by an
 		    /// extended number of type Value, i.e. a finite number of type
 		    /// Value or \ref INF.
 		    virtual void _setRowUpperBound(int i, Value value);
 		    /// \e
 		    /// The upper bound of a constraint (row) is an
 		    /// extended number of type Value, i.e. a finite number of type
 		    /// Value or \ref INF.
 		    virtual Value _getRowUpperBound(int i) const;
 		    /// \e
 		    virtual void _setObjCoeffs(ExprIterator b, ExprIterator e);
 		    /// \e
 		    virtual void _getObjCoeffs(InsertIterator b) const;
 		    /// \e
 		    virtual void _setObjCoeff(int i, Value obj_coef);
 		    /// \e
 		    virtual Value _getObjCoeff(int i) const;
 		    ///\e
 		    virtual void _setSense(Sense);
 		    ///\e
 		    virtual Sense _getSense() const;
 		    ///\e
 		    virtual void _clear();
 		  };
-		  /// \brief Interface for a skeleton LP solver
+		  /// \brief Skeleton class for an LP solver interface
 		  ///
-		  /// This class implements an interface for a skeleton LP solver.
+		  ///This class does nothing, but it can serve as a skeleton when
 		  ///implementing an interface to new solvers.
 		  ///\ingroup lp_group
-		  class LpSkeleton : public SkeletonSolverBase, public LpSolver {
+		  class LpSkeleton : public LpSolver, public SkeletonSolverBase {
 		  public:
 		    LpSkeleton() : SkeletonSolverBase(), LpSolver() {}
 		    ///\e
 		    LpSkeleton() : LpSolver(), SkeletonSolverBase() {}
 		    ///\e
 		    virtual LpSkeleton* newSolver() const;
 		    ///\e
 		    virtual LpSkeleton* cloneSolver() const;
 		  protected:
 		    ///\e
 		    virtual SolveExitStatus _solve();
 		    ///\e
 		    virtual Value _getPrimal(int i) const;
 		    ///\e
 		    virtual Value _getDual(int i) const;
 		    ///\e
 		    virtual Value _getPrimalValue() const;
 		    ///\e
 		    virtual Value _getPrimalRay(int i) const;
 		    ///\e
 		    virtual Value _getDualRay(int i) const;
 		    ///\e
 		    virtual ProblemType _getPrimalType() const;
 		    ///\e
 		    virtual ProblemType _getDualType() const;
 		    ///\e
 		    virtual VarStatus _getColStatus(int i) const;
 		    ///\e
 		    virtual VarStatus _getRowStatus(int i) const;
 		    ///\e
 		    virtual LpSkeleton* _newSolver() const;
 		    ///\e
 		    virtual LpSkeleton* _cloneSolver() const;
 		    ///\e
 		    virtual const char* _solverName() const;
 		  };
-		  /// \brief Interface for a skeleton MIP solver
+		  /// \brief Skeleton class for a MIP solver interface
 		  ///
-		  /// This class implements an interface for a skeleton MIP solver.
+		  ///This class does nothing, but it can serve as a skeleton when
 		  ///implementing an interface to new solvers.
 		  ///\ingroup lp_group
-		  class MipSkeleton : public SkeletonSolverBase, public MipSolver {
+		  class MipSkeleton : public MipSolver, public SkeletonSolverBase {
 		  public:
-		    MipSkeleton() : SkeletonSolverBase(), MipSolver() {}
+		    ///\e
 		    MipSkeleton() : MipSolver(), SkeletonSolverBase() {}
 		    ///\e
 		    virtual MipSkeleton* newSolver() const;
 		    ///\e
 		    virtual MipSkeleton* cloneSolver() const;
 		  protected:
 		    ///\e
 		    ///\bug Wrong interface
 		    ///
 		    virtual SolveExitStatus _solve();
 		    ///\e
 		    ///\bug Wrong interface
 		    ///
 		    virtual Value _getSol(int i) const;
 		    ///\e
 		    ///\bug Wrong interface
 		    ///
 		    virtual Value _getSolValue() const;
 		    ///\e
 		    ///\bug Wrong interface
 		    ///
 		    virtual ProblemType _getType() const;
 		    ///\e
 		    virtual MipSkeleton* _newSolver() const;
 		    ///\e
 		    virtual MipSkeleton* _cloneSolver() const;
 		    ///\e
 		    virtual const char* _solverName() const;
 		  };
 		} //namespace lemon
 		#endif

lemon/soplex.cc

Show inline comments

/* -*- mode: C++; indent-tabs-mode: nil; -*-
 *
 * This file is a part of LEMON, a generic C++ optimization library.
 *
 * Copyright (C) 2003-2008
 * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
 * (Egervary Research Group on Combinatorial Optimization, EGRES).
 *
 * Permission to use, modify and distribute this software is granted
 * provided that this copyright notice appears in all copies. For
 * precise terms see the accompanying LICENSE file.
 *
 * This software is provided "AS IS" with no warranty of any kind,
 * express or implied, and with no claim as to its suitability for any
 * purpose.
 *
 */

#include <iostream>
#include <lemon/soplex.h>

#include <soplex.h>


///\file
///\brief Implementation of the LEMON-SOPLEX lp solver interface.
namespace lemon {

  SoplexLp::SoplexLp() {
    soplex = new soplex::SoPlex;
  }

  SoplexLp::~SoplexLp() {
    delete soplex;
  }

  SoplexLp::SoplexLp(const SoplexLp& lp) {
    rows = lp.rows;
    cols = lp.cols;

    soplex = new soplex::SoPlex;
    (*static_cast<soplex::SPxLP*>(soplex)) = *(lp.soplex);

    _col_names = lp._col_names;
    _col_names_ref = lp._col_names_ref;

    _row_names = lp._row_names;
    _row_names_ref = lp._row_names_ref;

  }

  void SoplexLp::_clear_temporals() {
    _primal_values.clear();
    _dual_values.clear();
  }

  SoplexLp* SoplexLp::_newSolver() const {
  SoplexLp* SoplexLp::newSolver() const {
    SoplexLp* newlp = new SoplexLp();
    return newlp;
  }

  SoplexLp* SoplexLp::_cloneSolver() const {
  SoplexLp* SoplexLp::cloneSolver() const {
    SoplexLp* newlp = new SoplexLp(*this);
    return newlp;
  }

  const char* SoplexLp::_solverName() const { return "SoplexLp"; }

  int SoplexLp::_addCol() {
    soplex::LPCol c;
    c.setLower(-soplex::infinity);
    c.setUpper(soplex::infinity);
    soplex->addCol(c);

    _col_names.push_back(std::string());

    return soplex->nCols() - 1;
  }

  int SoplexLp::_addRow() {
    soplex::LPRow r;
    r.setLhs(-soplex::infinity);
    r.setRhs(soplex::infinity);
    soplex->addRow(r);

    _row_names.push_back(std::string());

    return soplex->nRows() - 1;
  }


  void SoplexLp::_eraseCol(int i) {
    soplex->removeCol(i);
    _col_names_ref.erase(_col_names[i]);
    _col_names[i] = _col_names.back();
    _col_names_ref[_col_names.back()] = i;
    _col_names.pop_back();
  }

  void SoplexLp::_eraseRow(int i) {
    soplex->removeRow(i);
    _row_names_ref.erase(_row_names[i]);
    _row_names[i] = _row_names.back();
    _row_names_ref[_row_names.back()] = i;
    _row_names.pop_back();
  }

  void SoplexLp::_eraseColId(int i) {
    cols.eraseIndex(i);
    cols.relocateIndex(i, cols.maxIndex());
  }
  void SoplexLp::_eraseRowId(int i) {
    rows.eraseIndex(i);
    rows.relocateIndex(i, rows.maxIndex());
  }

  void SoplexLp::_getColName(int c, std::string &name) const {
    name = _col_names[c];
  }

  void SoplexLp::_setColName(int c, const std::string &name) {
    _col_names_ref.erase(_col_names[c]);
    _col_names[c] = name;
    if (!name.empty()) {
      _col_names_ref.insert(std::make_pair(name, c));
    }
  }

  int SoplexLp::_colByName(const std::string& name) const {
    std::map<std::string, int>::const_iterator it =
      _col_names_ref.find(name);
    if (it != _col_names_ref.end()) {
      return it->second;
    } else {
      return -1;
    }
  }

  void SoplexLp::_getRowName(int r, std::string &name) const {
    name = _row_names[r];
  }

  void SoplexLp::_setRowName(int r, const std::string &name) {
    _row_names_ref.erase(_row_names[r]);
    _row_names[r] = name;
    if (!name.empty()) {
      _row_names_ref.insert(std::make_pair(name, r));
    }
  }

  int SoplexLp::_rowByName(const std::string& name) const {
    std::map<std::string, int>::const_iterator it =
      _row_names_ref.find(name);
    if (it != _row_names_ref.end()) {
      return it->second;
    } else {
      return -1;
    }
  }


  void SoplexLp::_setRowCoeffs(int i, ExprIterator b, ExprIterator e) {
    for (int j = 0; j < soplex->nCols(); ++j) {
      soplex->changeElement(i, j, 0.0);
    }
    for(ExprIterator it = b; it != e; ++it) {
      soplex->changeElement(i, it->first, it->second);
    }
  }

  void SoplexLp::_getRowCoeffs(int i, InsertIterator b) const {
    const soplex::SVector& vec = soplex->rowVector(i);
    for (int k = 0; k < vec.size(); ++k) {
      *b = std::make_pair(vec.index(k), vec.value(k));
      ++b;
    }
  }

  void SoplexLp::_setColCoeffs(int j, ExprIterator b, ExprIterator e) {
    for (int i = 0; i < soplex->nRows(); ++i) {
      soplex->changeElement(i, j, 0.0);
    }
    for(ExprIterator it = b; it != e; ++it) {
      soplex->changeElement(it->first, j, it->second);
    }
  }

  void SoplexLp::_getColCoeffs(int i, InsertIterator b) const {
    const soplex::SVector& vec = soplex->colVector(i);
    for (int k = 0; k < vec.size(); ++k) {
      *b = std::make_pair(vec.index(k), vec.value(k));
      ++b;
    }
  }

  void SoplexLp::_setCoeff(int i, int j, Value value) {
    soplex->changeElement(i, j, value);
  }

  SoplexLp::Value SoplexLp::_getCoeff(int i, int j) const {
    return soplex->rowVector(i)[j];
  }

  void SoplexLp::_setColLowerBound(int i, Value value) {
    LEMON_ASSERT(value != INF, "Invalid bound");
    soplex->changeLower(i, value != -INF ? value : -soplex::infinity);
  }

  SoplexLp::Value SoplexLp::_getColLowerBound(int i) const {
    double value = soplex->lower(i);
    return value != -soplex::infinity ? value : -INF;
  }

  void SoplexLp::_setColUpperBound(int i, Value value) {
    LEMON_ASSERT(value != -INF, "Invalid bound");
    soplex->changeUpper(i, value != INF ? value : soplex::infinity);
  }

  SoplexLp::Value SoplexLp::_getColUpperBound(int i) const {
    double value = soplex->upper(i);
    return value != soplex::infinity ? value : INF;
  }

  void SoplexLp::_setRowLowerBound(int i, Value lb) {
    LEMON_ASSERT(lb != INF, "Invalid bound");
    soplex->changeRange(i, lb != -INF ? lb : -soplex::infinity, soplex->rhs(i));
  }

  SoplexLp::Value SoplexLp::_getRowLowerBound(int i) const {
    double res = soplex->lhs(i);
    return res == -soplex::infinity ? -INF : res;
  }

  void SoplexLp::_setRowUpperBound(int i, Value ub) {
    LEMON_ASSERT(ub != -INF, "Invalid bound");
    soplex->changeRange(i, soplex->lhs(i), ub != INF ? ub : soplex::infinity);
  }

  SoplexLp::Value SoplexLp::_getRowUpperBound(int i) const {
    double res = soplex->rhs(i);
    return res == soplex::infinity ? INF : res;
  }

  void SoplexLp::_setObjCoeffs(ExprIterator b, ExprIterator e) {
    for (int j = 0; j < soplex->nCols(); ++j) {
      soplex->changeObj(j, 0.0);
    }
    for (ExprIterator it = b; it != e; ++it) {
      soplex->changeObj(it->first, it->second);
    }
  }

  void SoplexLp::_getObjCoeffs(InsertIterator b) const {
    for (int j = 0; j < soplex->nCols(); ++j) {

lemon/soplex.h

Show inline comments

 		/* -*- mode: C++; indent-tabs-mode: nil; -*-
+		 *
 		 * This file is a part of LEMON, a generic C++ optimization library.
+		 *
 		 * Copyright (C) 2003-2008
 		 * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
 		 * (Egervary Research Group on Combinatorial Optimization, EGRES).
+		 *
 		 * Permission to use, modify and distribute this software is granted
 		 * provided that this copyright notice appears in all copies. For
 		 * precise terms see the accompanying LICENSE file.
+		 *
 		 * This software is provided "AS IS" with no warranty of any kind,
 		 * express or implied, and with no claim as to its suitability for any
 		 * purpose.
+		 *
 		 */
 		#ifndef LEMON_SOPLEX_H
 		#define LEMON_SOPLEX_H
 		///\file
 		///\brief Header of the LEMON-SOPLEX lp solver interface.
 		#include <vector>
 		#include <string>
 		#include <lemon/lp_base.h>
 		// Forward declaration
 		namespace soplex {
 		  class SoPlex;
+		}
 		namespace lemon {
 		  /// \ingroup lp_group
 		  ///
 		  /// \brief Interface for the SOPLEX solver
 		  ///
 		  /// This class implements an interface for the SoPlex LP solver.
 		  /// The SoPlex library is an object oriented lp solver library
 		  /// developed at the Konrad-Zuse-Zentrum f�r Informationstechnik
 		  /// Berlin (ZIB). You can find detailed information about it at the
 		  /// <tt>http://soplex.zib.de</tt> address.
 		  class SoplexLp : public LpSolver {
 		  private:
 		    soplex::SoPlex* soplex;
 		    std::vector<std::string> _col_names;
 		    std::map<std::string, int> _col_names_ref;
 		    std::vector<std::string> _row_names;
 		    std::map<std::string, int> _row_names_ref;
 		  private:
 		    // these values cannot be retrieved element by element
 		    mutable std::vector<Value> _primal_values;
 		    mutable std::vector<Value> _dual_values;
 		    mutable std::vector<Value> _primal_ray;
 		    mutable std::vector<Value> _dual_ray;
 		    void _clear_temporals();
 		  public:
 		    /// \e
 		    SoplexLp();
 		    /// \e
 		    SoplexLp(const SoplexLp&);
 		    /// \e
 		    ~SoplexLp();
 		    /// \e
 		    virtual SoplexLp* newSolver() const;
 		    /// \e
 		    virtual SoplexLp* cloneSolver() const;
 		  protected:
 		    virtual SoplexLp* _newSolver() const;
 		    virtual SoplexLp* _cloneSolver() const;
 		    virtual const char* _solverName() const;
 		    virtual int _addCol();
 		    virtual int _addRow();
 		    virtual void _eraseCol(int i);
 		    virtual void _eraseRow(int i);
 		    virtual void _eraseColId(int i);
 		    virtual void _eraseRowId(int i);
 		    virtual void _getColName(int col, std::string& name) const;
 		    virtual void _setColName(int col, const std::string& name);
 		    virtual int _colByName(const std::string& name) const;
 		    virtual void _getRowName(int row, std::string& name) const;
 		    virtual void _setRowName(int row, const std::string& name);
 		    virtual int _rowByName(const std::string& name) const;
 		    virtual void _setRowCoeffs(int i, ExprIterator b, ExprIterator e);
 		    virtual void _getRowCoeffs(int i, InsertIterator b) const;
 		    virtual void _setColCoeffs(int i, ExprIterator b, ExprIterator e);
 		    virtual void _getColCoeffs(int i, InsertIterator b) const;
 		    virtual void _setCoeff(int row, int col, Value value);
 		    virtual Value _getCoeff(int row, int col) const;
 		    virtual void _setColLowerBound(int i, Value value);
 		    virtual Value _getColLowerBound(int i) const;
 		    virtual void _setColUpperBound(int i, Value value);
 		    virtual Value _getColUpperBound(int i) const;
 		    virtual void _setRowLowerBound(int i, Value value);
 		    virtual Value _getRowLowerBound(int i) const;
 		    virtual void _setRowUpperBound(int i, Value value);
 		    virtual Value _getRowUpperBound(int i) const;
 		    virtual void _setObjCoeffs(ExprIterator b, ExprIterator e);
 		    virtual void _getObjCoeffs(InsertIterator b) const;
 		    virtual void _setObjCoeff(int i, Value obj_coef);
 		    virtual Value _getObjCoeff(int i) const;
 		    virtual void _setSense(Sense sense);
 		    virtual Sense _getSense() const;
 		    virtual SolveExitStatus _solve();
 		    virtual Value _getPrimal(int i) const;
 		    virtual Value _getDual(int i) const;
 		    virtual Value _getPrimalValue() const;
 		    virtual Value _getPrimalRay(int i) const;
 		    virtual Value _getDualRay(int i) const;
 		    virtual VarStatus _getColStatus(int i) const;
 		    virtual VarStatus _getRowStatus(int i) const;
 		    virtual ProblemType _getPrimalType() const;
 		    virtual ProblemType _getDualType() const;
 		    virtual void _clear();
 		  };
 		} //END OF NAMESPACE LEMON
 		#endif //LEMON_SOPLEX_H

test/lp_test.cc

Show inline comments

@@ -8,396 +8,419 @@
+		 *
 		 * Permission to use, modify and distribute this software is granted
 		 * provided that this copyright notice appears in all copies. For
 		 * precise terms see the accompanying LICENSE file.
+		 *
 		 * This software is provided "AS IS" with no warranty of any kind,
 		 * express or implied, and with no claim as to its suitability for any
 		 * purpose.
+		 *
 		 */
 		#include <sstream>
 		#include <lemon/lp_skeleton.h>
 		#include "test_tools.h"
 		#include <lemon/tolerance.h>
 		#ifdef HAVE_CONFIG_H
 		#include <lemon/config.h>
 		#endif
 		#ifdef HAVE_GLPK
 		#include <lemon/glpk.h>
 		#endif
 		#ifdef HAVE_CPLEX
 		#include <lemon/cplex.h>
 		#endif
 		#ifdef HAVE_SOPLEX
 		#include <lemon/soplex.h>
 		#endif
 		#ifdef HAVE_CLP
 		#include <lemon/clp.h>
 		#endif
 		using namespace lemon;
 		void lpTest(LpSolver& lp)
+		{
 		  typedef LpSolver LP;
 		  std::vector<LP::Col> x(10);
 		  //  for(int i=0;i<10;i++) x.push_back(lp.addCol());
 		  lp.addColSet(x);
 		  lp.colLowerBound(x,1);
 		  lp.colUpperBound(x,1);
 		  lp.colBounds(x,1,2);
 		  std::vector<LP::Col> y(10);
 		  lp.addColSet(y);
 		  lp.colLowerBound(y,1);
 		  lp.colUpperBound(y,1);
 		  lp.colBounds(y,1,2);
 		  std::map<int,LP::Col> z;
 		  z.insert(std::make_pair(12,INVALID));
 		  z.insert(std::make_pair(2,INVALID));
 		  z.insert(std::make_pair(7,INVALID));
 		  z.insert(std::make_pair(5,INVALID));
 		  lp.addColSet(z);
 		  lp.colLowerBound(z,1);
 		  lp.colUpperBound(z,1);
 		  lp.colBounds(z,1,2);
+		  {
 		    LP::Expr e,f,g;
 		    LP::Col p1,p2,p3,p4,p5;
 		    LP::Constr c;
 		    p1=lp.addCol();
 		    p2=lp.addCol();
 		    p3=lp.addCol();
 		    p4=lp.addCol();
 		    p5=lp.addCol();
 		    e[p1]=2;
 		    *e=12;
 		    e[p1]+=2;
 		    *e+=12;
 		    e[p1]-=2;
 		    *e-=12;
 		    e=2;
 		    e=2.2;
 		    e=p1;
 		    e=f;
 		    e+=2;
 		    e+=2.2;
 		    e+=p1;
 		    e+=f;
 		    e-=2;
 		    e-=2.2;
 		    e-=p1;
 		    e-=f;
 		    e*=2;
 		    e*=2.2;
 		    e/=2;
 		    e/=2.2;
 		    e=((p1+p2)+(p1-p2)+(p1+12)+(12+p1)+(p1-12)+(12-p1)+
 		       (f+12)+(12+f)+(p1+f)+(f+p1)+(f+g)+
 		       (f-12)+(12-f)+(p1-f)+(f-p1)+(f-g)+
 .2*f+f*2.2+f/2.2+
 *f+f*2+f/2+
 .2*p1+p1*2.2+p1/2.2+
 *p1+p1*2+p1/2
 		       );
 		    c = (e  <= f  );
 		    c = (e  <= 2.2);
 		    c = (e  <= 2  );
 		    c = (e  <= p1 );
 		    c = (2.2<= f  );
 		    c = (2  <= f  );
 		    c = (p1 <= f  );
 		    c = (p1 <= p2 );
 		    c = (p1 <= 2.2);
 		    c = (p1 <= 2  );
 		    c = (2.2<= p2 );
 		    c = (2  <= p2 );
 		    c = (e  >= f  );
 		    c = (e  >= 2.2);
 		    c = (e  >= 2  );
 		    c = (e  >= p1 );
 		    c = (2.2>= f  );
 		    c = (2  >= f  );
 		    c = (p1 >= f  );
 		    c = (p1 >= p2 );
 		    c = (p1 >= 2.2);
 		    c = (p1 >= 2  );
 		    c = (2.2>= p2 );
 		    c = (2  >= p2 );
 		    c = (e  == f  );
 		    c = (e  == 2.2);
 		    c = (e  == 2  );
 		    c = (e  == p1 );
 		    c = (2.2== f  );
 		    c = (2  == f  );
 		    c = (p1 == f  );
 		    //c = (p1 == p2 );
 		    c = (p1 == 2.2);
 		    c = (p1 == 2  );
 		    c = (2.2== p2 );
 		    c = (2  == p2 );
 		    c = ((2 <= e) <= 3);
 		    c = ((2 <= p1) <= 3);
 		    c = ((2 >= e) >= 3);
 		    c = ((2 >= p1) >= 3);
 		    e[x[3]]=2;
 		    e[x[3]]=4;
 		    e[x[3]]=1;
 		    *e=12;
 		    lp.addRow(-LP::INF,e,23);
 		    lp.addRow(-LP::INF,3.0*(x[1]+x[2]/2)-x[3],23);
 		    lp.addRow(-LP::INF,3.0*(x[1]+x[2]*2-5*x[3]+12-x[4]/3)+2*x[4]-4,23);
 		    lp.addRow(x[1]+x[3]<=x[5]-3);
 		    lp.addRow((-7<=x[1]+x[3]-12)<=3);
 		    lp.addRow(x[1]<=x[5]);
 		    std::ostringstream buf;
 		    e=((p1+p2)+(p1-0.99*p2));
 		    //e.prettyPrint(std::cout);
 		    //(e<=2).prettyPrint(std::cout);
 		    double tolerance=0.001;
 		    e.simplify(tolerance);
 		    buf << "Coeff. of p2 should be 0.01";
 		    check(e[p2]>0, buf.str());
 		    tolerance=0.02;
 		    e.simplify(tolerance);
 		    buf << "Coeff. of p2 should be 0";
 		    check(const_cast<const LpSolver::Expr&>(e)[p2]==0, buf.str());
 		    //Test for clone/new
 		    LP* lpnew = lp.newSolver();
 		    LP* lpclone = lp.cloneSolver();
 		    delete lpnew;
 		    delete lpclone;
+		  }
+		  {
 		    LP::DualExpr e,f,g;
 		    LP::Row p1 = INVALID, p2 = INVALID, p3 = INVALID,
 		      p4 = INVALID, p5 = INVALID;
 		    e[p1]=2;
 		    e[p1]+=2;
 		    e[p1]-=2;
 		    e=p1;
 		    e=f;
 		    e+=p1;
 		    e+=f;
 		    e-=p1;
 		    e-=f;
 		    e*=2;
 		    e*=2.2;
 		    e/=2;
 		    e/=2.2;
 		    e=((p1+p2)+(p1-p2)+
 		       (p1+f)+(f+p1)+(f+g)+
 		       (p1-f)+(f-p1)+(f-g)+
 .2*f+f*2.2+f/2.2+
 *f+f*2+f/2+
 .2*p1+p1*2.2+p1/2.2+
 *p1+p1*2+p1/2
 		       );
+		  }
+		}
 		void solveAndCheck(LpSolver& lp, LpSolver::ProblemType stat,
 		                   double exp_opt) {
 		  using std::string;
 		  lp.solve();
 		  std::ostringstream buf;
 		  buf << "PrimalType should be: " << int(stat) << int(lp.primalType());
 		  check(lp.primalType()==stat, buf.str());
 		  if (stat ==  LpSolver::OPTIMAL) {
 		    std::ostringstream sbuf;
-		    sbuf << "Wrong optimal value: the right optimum is " << exp_opt;
+		    sbuf << "Wrong optimal value (" << lp.primal() <<") with "
 		         << lp.solverName() <<"\n     the right optimum is " << exp_opt;
 		    check(std::abs(lp.primal()-exp_opt) < 1e-3, sbuf.str());
+		  }
+		}
 		void aTest(LpSolver & lp)
+		{
 		  typedef LpSolver LP;
 		 //The following example is very simple
 		  typedef LpSolver::Row Row;
 		  typedef LpSolver::Col Col;
 		  Col x1 = lp.addCol();
 		  Col x2 = lp.addCol();
 		  //Constraints
 		  Row upright=lp.addRow(x1+2*x2 <=1);
 		  lp.addRow(x1+x2 >=-1);
 		  lp.addRow(x1-x2 <=1);
 		  lp.addRow(x1-x2 >=-1);
 		  //Nonnegativity of the variables
 		  lp.colLowerBound(x1, 0);
 		  lp.colLowerBound(x2, 0);
 		  //Objective function
 		  lp.obj(x1+x2);
 		  lp.sense(lp.MAX);
 		  //Testing the problem retrieving routines
 		  check(lp.objCoeff(x1)==1,"First term should be 1 in the obj function!");
 		  check(lp.sense() == lp.MAX,"This is a maximization!");
 		  check(lp.coeff(upright,x1)==1,"The coefficient in question is 1!");
 		  check(lp.colLowerBound(x1)==0,
 		        "The lower bound for variable x1 should be 0.");
 		  check(lp.colUpperBound(x1)==LpSolver::INF,
 		        "The upper bound for variable x1 should be infty.");
 		  check(lp.rowLowerBound(upright) == -LpSolver::INF,
 		        "The lower bound for the first row should be -infty.");
 		  check(lp.rowUpperBound(upright)==1,
 		        "The upper bound for the first row should be 1.");
 		  LpSolver::Expr e = lp.row(upright);
 		  check(e[x1] == 1, "The first coefficient should 1.");
 		  check(e[x2] == 2, "The second coefficient should 1.");
 		  lp.row(upright, x1+x2 <=1);
 		  e = lp.row(upright);
 		  check(e[x1] == 1, "The first coefficient should 1.");
 		  check(e[x2] == 1, "The second coefficient should 1.");
 		  LpSolver::DualExpr de = lp.col(x1);
 		  check(  de[upright] == 1, "The first coefficient should 1.");
 		  LpSolver* clp = lp.cloneSolver();
 		  //Testing the problem retrieving routines
 		  check(clp->objCoeff(x1)==1,"First term should be 1 in the obj function!");
 		  check(clp->sense() == clp->MAX,"This is a maximization!");
 		  check(clp->coeff(upright,x1)==1,"The coefficient in question is 1!");
 		  //  std::cout<<lp.colLowerBound(x1)<<std::endl;
 		  check(clp->colLowerBound(x1)==0,
 		        "The lower bound for variable x1 should be 0.");
 		  check(clp->colUpperBound(x1)==LpSolver::INF,
 		        "The upper bound for variable x1 should be infty.");
 		  check(lp.rowLowerBound(upright)==-LpSolver::INF,
 		        "The lower bound for the first row should be -infty.");
 		  check(lp.rowUpperBound(upright)==1,
 		        "The upper bound for the first row should be 1.");
 		  e = clp->row(upright);
 		  check(e[x1] == 1, "The first coefficient should 1.");
 		  check(e[x2] == 1, "The second coefficient should 1.");
 		  de = clp->col(x1);
 		  check(de[upright] == 1, "The first coefficient should 1.");
 		  delete clp;
 		  //Maximization of x1+x2
 		  //over the triangle with vertices (0,0) (0,1) (1,0)
 		  double expected_opt=1;
 		  solveAndCheck(lp, LpSolver::OPTIMAL, expected_opt);
 		  //Minimization
 		  lp.sense(lp.MIN);
 		  expected_opt=0;
 		  solveAndCheck(lp, LpSolver::OPTIMAL, expected_opt);
 		  //Vertex (-1,0) instead of (0,0)
 		  lp.colLowerBound(x1, -LpSolver::INF);
 		  expected_opt=-1;
 		  solveAndCheck(lp, LpSolver::OPTIMAL, expected_opt);
 		  //Erase one constraint and return to maximization
 		  lp.erase(upright);
 		  lp.sense(lp.MAX);
 		  expected_opt=LpSolver::INF;
 		  solveAndCheck(lp, LpSolver::UNBOUNDED, expected_opt);
 		  //Infeasibilty
 		  lp.addRow(x1+x2 <=-2);
 		  solveAndCheck(lp, LpSolver::INFEASIBLE, expected_opt);
+		}
 		template<class LP>
 		void cloneTest()
+		{
 		  //Test for clone/new
 		  LP* lp = new LP();
 		  LP* lpnew = lp->newSolver();
 		  LP* lpclone = lp->cloneSolver();
 		  delete lp;
 		  delete lpnew;
 		  delete lpclone;
+		}
 		int main()
+		{
 		  LpSkeleton lp_skel;
 		  lpTest(lp_skel);
 		#ifdef HAVE_GLPK
+		  {
 		    GlpkLp lp_glpk1,lp_glpk2;
 		    lpTest(lp_glpk1);
 		    aTest(lp_glpk2);
 		    cloneTest<GlpkLp>();
+		  }
 		#endif
 		#ifdef HAVE_CPLEX
 		  try {
 		    CplexLp lp_cplex1,lp_cplex2;
 		    lpTest(lp_cplex1);
 		    aTest(lp_cplex2);
 		  } catch (CplexEnv::LicenseError& error) {
 		#ifdef LEMON_FORCE_CPLEX_CHECK
 		    check(false, error.what());
 		#else
 		    std::cerr << error.what() << std::endl;
 		    std::cerr << "Cplex license check failed, lp check skipped" << std::endl;
 		#endif
+		  }
 		    cloneTest<CplexLp>();
 		#endif
 		#ifdef HAVE_SOPLEX
+		  {
 		    SoplexLp lp_soplex1,lp_soplex2;
 		    lpTest(lp_soplex1);
 		    aTest(lp_soplex2);
 		    cloneTest<SoplexLp>();
+		  }
 		#endif
 		#ifdef HAVE_CLP
+		  {
 		    ClpLp lp_clp1,lp_clp2;
 		    lpTest(lp_clp1);
 		    aTest(lp_clp2);
 		    cloneTest<ClpLp>();
+		  }
 		#endif
 		  return 0;
+		}

test/mip_test.cc

Show inline comments

 		/* -*- mode: C++; indent-tabs-mode: nil; -*-
+		 *
 		 * This file is a part of LEMON, a generic C++ optimization library.
+		 *
 		 * Copyright (C) 2003-2008
 		 * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
 		 * (Egervary Research Group on Combinatorial Optimization, EGRES).
+		 *
 		 * Permission to use, modify and distribute this software is granted
 		 * provided that this copyright notice appears in all copies. For
 		 * precise terms see the accompanying LICENSE file.
+		 *
 		 * This software is provided "AS IS" with no warranty of any kind,
 		 * express or implied, and with no claim as to its suitability for any
 		 * purpose.
+		 *
 		 */
 		#include "test_tools.h"
 		#ifdef HAVE_CONFIG_H
 		#include <lemon/config.h>
 		#endif
 		#ifdef HAVE_CPLEX
 		#include <lemon/cplex.h>
 		#endif
 		#ifdef HAVE_GLPK
 		#include <lemon/glpk.h>
 		#endif
 		using namespace lemon;
 		void solveAndCheck(MipSolver& mip, MipSolver::ProblemType stat,
 		                   double exp_opt) {
 		  using std::string;
 		  mip.solve();
 		  //int decimal,sign;
 		  std::ostringstream buf;
 		  buf << "Type should be: " << int(stat)<<" and it is "<<int(mip.type());
 		  //  itoa(stat,buf1, 10);
 		  check(mip.type()==stat, buf.str());
 		  if (stat ==  MipSolver::OPTIMAL) {
 		    std::ostringstream sbuf;
 		    buf << "Wrong optimal value: the right optimum is " << exp_opt;
 		    check(std::abs(mip.solValue()-exp_opt) < 1e-3, sbuf.str());
 		    //+ecvt(exp_opt,2)
+		  }
+		}
 		void aTest(MipSolver& mip)
+		{
 		 //The following example is very simple
 		  typedef MipSolver::Row Row;
 		  typedef MipSolver::Col Col;
 		  Col x1 = mip.addCol();
 		  Col x2 = mip.addCol();
 		  //Objective function
 		  mip.obj(x1);
 		  mip.max();
 		  //Unconstrained optimization
 		  mip.solve();
 		  //Check it out!
 		  //Constraints
 		  mip.addRow(2*x1+x2 <=2);
 		  mip.addRow(x1-2*x2 <=0);
 		  //Nonnegativity of the variable x1
 		  mip.colLowerBound(x1, 0);
 		  //Maximization of x1
 		  //over the triangle with vertices (0,0),(4/5,2/5),(0,2)
 		  double expected_opt=4.0/5.0;
 		  solveAndCheck(mip, MipSolver::OPTIMAL, expected_opt);
 		  //Restrict x2 to integer
 		  mip.colType(x2,MipSolver::INTEGER);
 		  expected_opt=1.0/2.0;
 		  solveAndCheck(mip, MipSolver::OPTIMAL, expected_opt);
 		  //Restrict both to integer
 		  mip.colType(x1,MipSolver::INTEGER);
 		  expected_opt=0;
 		  solveAndCheck(mip, MipSolver::OPTIMAL, expected_opt);
+		}
 		template<class MIP>
 		void cloneTest()
+		{
 		  MIP* mip = new MIP();
 		  MIP* mipnew = mip->newSolver();
 		  MIP* mipclone = mip->cloneSolver();
 		  delete mip;
 		  delete mipnew;
 		  delete mipclone;
+		}
 		int main()
+		{
 		#ifdef HAVE_GLPK
+		  {
 		    GlpkMip mip1;
 		    aTest(mip1);
 		    cloneTest<GlpkMip>();
+		  }
 		#endif
 		#ifdef HAVE_CPLEX
 		  try {
 		    CplexMip mip2;
 		    aTest(mip2);
 		  } catch (CplexEnv::LicenseError& error) {
 		#ifdef LEMON_FORCE_CPLEX_CHECK
 		    check(false, error.what());
 		#else
 		    std::cerr << error.what() << std::endl;
 		    std::cerr << "Cplex license check failed, lp check skipped" << std::endl;
 		#endif
+		  }
 		  cloneTest<CplexMip>();
 		#endif
 		  return 0;
+		}

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1	1	/* -- mode: C++; indent-tabs-mode: nil; --
2	2	*
3	3	* This file is a part of LEMON, a generic C++ optimization library.
4	4	*
5	5	* Copyright (C) 2003-2008
6	6	* Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
7	7	* (Egervary Research Group on Combinatorial Optimization, EGRES).
8	8	*
9	9	* Permission to use, modify and distribute this software is granted
10	10	* provided that this copyright notice appears in all copies. For
11	11	* precise terms see the accompanying LICENSE file.
12	12	*
13	13	* This software is provided "AS IS" with no warranty of any kind,
14	14	* express or implied, and with no claim as to its suitability for any
15	15	* purpose.
16	16	*
17	17	*/
18	18
19	19	#include <lemon/clp.h>
20	20	#include <coin/ClpSimplex.hpp>
21	21
22	22	namespace lemon {
23	23
24	24	ClpLp::ClpLp() {
25	25	_prob = new ClpSimplex();
26	26	_init_temporals();
27	27	messageLevel(MESSAGE_NO_OUTPUT);
28	28	}
29	29
30	30	ClpLp::ClpLp(const ClpLp& other) {
31	31	_prob = new ClpSimplex(*other._prob);
32	32	rows = other.rows;
33	33	cols = other.cols;
34	34	_init_temporals();
35	35	messageLevel(MESSAGE_NO_OUTPUT);
36	36	}
37	37
38	38	ClpLp::~ClpLp() {
39	39	delete _prob;
40	40	_clear_temporals();
41	41	}
42	42
43	43	void ClpLp::_init_temporals() {
44	44	_primal_ray = 0;
45	45	_dual_ray = 0;
46	46	}
47	47
48	48	void ClpLp::_clear_temporals() {
49	49	if (_primal_ray) {
50	50	delete[] _primal_ray;
51	51	_primal_ray = 0;
52	52	}
53	53	if (_dual_ray) {
54	54	delete[] _dual_ray;
55	55	_dual_ray = 0;
56	56	}
57	57	}
58	58
59		ClpLp* ClpLp::~~_newSolver~~() const {
	59	ClpLp* ClpLp::newSolver() const {
60	60	ClpLp* newlp = new ClpLp;
61	61	return newlp;
62	62	}
63	63
64		ClpLp* ClpLp::~~_cloneSolver~~() const {
	64	ClpLp* ClpLp::cloneSolver() const {
65	65	ClpLp* copylp = new ClpLp(*this);
66	66	return copylp;
67	67	}
68	68
69	69	const char* ClpLp::_solverName() const { return "ClpLp"; }
70	70
71	71	int ClpLp::_addCol() {
72	72	_prob->addColumn(0, 0, 0, -COIN_DBL_MAX, COIN_DBL_MAX, 0.0);
73	73	return _prob->numberColumns() - 1;
74	74	}
75	75
76	76	int ClpLp::_addRow() {
77	77	_prob->addRow(0, 0, 0, -COIN_DBL_MAX, COIN_DBL_MAX);
78	78	return _prob->numberRows() - 1;
79	79	}
80	80
81	81
82	82	void ClpLp::_eraseCol(int c) {
83	83	_col_names_ref.erase(_prob->getColumnName(c));
84	84	_prob->deleteColumns(1, &c);
85	85	}
86	86
87	87	void ClpLp::_eraseRow(int r) {
88	88	_row_names_ref.erase(_prob->getRowName(r));
89	89	_prob->deleteRows(1, &r);
90	90	}
91	91
92	92	void ClpLp::_eraseColId(int i) {
93	93	cols.eraseIndex(i);
94	94	cols.shiftIndices(i);
95	95	}
96	96
97	97	void ClpLp::_eraseRowId(int i) {
98	98	rows.eraseIndex(i);
99	99	rows.shiftIndices(i);
100	100	}
101	101
102	102	void ClpLp::_getColName(int c, std::string& name) const {
103	103	name = _prob->getColumnName(c);
104	104	}
105	105
106	106	void ClpLp::_setColName(int c, const std::string& name) {
107	107	_prob->setColumnName(c, const_cast<std::string&>(name));
108	108	_col_names_ref[name] = c;
109	109	}
110	110
111	111	int ClpLp::_colByName(const std::string& name) const {
112	112	std::map<std::string, int>::const_iterator it = _col_names_ref.find(name);
113	113	return it != _col_names_ref.end() ? it->second : -1;
114	114	}
115	115
116	116	void ClpLp::_getRowName(int r, std::string& name) const {
117	117	name = _prob->getRowName(r);
118	118	}
119	119
120	120	void ClpLp::_setRowName(int r, const std::string& name) {
121	121	_prob->setRowName(r, const_cast<std::string&>(name));
122	122	_row_names_ref[name] = r;
123	123	}
124	124
125	125	int ClpLp::_rowByName(const std::string& name) const {
126	126	std::map<std::string, int>::const_iterator it = _row_names_ref.find(name);
127	127	return it != _row_names_ref.end() ? it->second : -1;
128	128	}
129	129
130	130
131	131	void ClpLp::_setRowCoeffs(int ix, ExprIterator b, ExprIterator e) {
132	132	std::map<int, Value> coeffs;
133	133
134	134	int n = _prob->clpMatrix()->getNumCols();
135	135
136	136	const int* indices = _prob->clpMatrix()->getIndices();
137	137	const double* elements = _prob->clpMatrix()->getElements();
138	138
139	139	for (int i = 0; i < n; ++i) {
140	140	CoinBigIndex begin = _prob->clpMatrix()->getVectorStarts()[i];
141	141	CoinBigIndex end = begin + _prob->clpMatrix()->getVectorLengths()[i];
142	142
143	143	const int* it = std::lower_bound(indices + begin, indices + end, ix);
144	144	if (it != indices + end && *it == ix && elements[it - indices] != 0.0) {
145	145	coeffs[i] = 0.0;
146	146	}
147	147	}
148	148
149	149	for (ExprIterator it = b; it != e; ++it) {
150	150	coeffs[it->first] = it->second;
151	151	}
152	152
153	153	for (std::map<int, Value>::iterator it = coeffs.begin();
154	154	it != coeffs.end(); ++it) {
155	155	_prob->modifyCoefficient(ix, it->first, it->second);
156	156	}
157	157	}
158	158
159	159	void ClpLp::_getRowCoeffs(int ix, InsertIterator b) const {
160	160	int n = _prob->clpMatrix()->getNumCols();
161	161
162	162	const int* indices = _prob->clpMatrix()->getIndices();
163	163	const double* elements = _prob->clpMatrix()->getElements();
164	164
165	165	for (int i = 0; i < n; ++i) {
166	166	CoinBigIndex begin = _prob->clpMatrix()->getVectorStarts()[i];
167	167	CoinBigIndex end = begin + _prob->clpMatrix()->getVectorLengths()[i];
168	168
169	169	const int* it = std::lower_bound(indices + begin, indices + end, ix);
170	170	if (it != indices + end && *it == ix) {
171	171	*b = std::make_pair(i, elements[it - indices]);
172	172	}
173	173	}
174	174	}
175	175
176	176	void ClpLp::_setColCoeffs(int ix, ExprIterator b, ExprIterator e) {
177	177	std::map<int, Value> coeffs;
178	178
179	179	CoinBigIndex begin = _prob->clpMatrix()->getVectorStarts()[ix];
180	180	CoinBigIndex end = begin + _prob->clpMatrix()->getVectorLengths()[ix];
181	181
182	182	const int* indices = _prob->clpMatrix()->getIndices();
183	183	const double* elements = _prob->clpMatrix()->getElements();
184	184
185	185	for (CoinBigIndex i = begin; i != end; ++i) {
186	186	if (elements[i] != 0.0) {
187	187	coeffs[indices[i]] = 0.0;
188	188	}
189	189	}
190	190	for (ExprIterator it = b; it != e; ++it) {
191	191	coeffs[it->first] = it->second;
192	192	}
193	193	for (std::map<int, Value>::iterator it = coeffs.begin();
194	194	it != coeffs.end(); ++it) {
195	195	_prob->modifyCoefficient(it->first, ix, it->second);
196	196	}
197	197	}
198	198
199	199	void ClpLp::_getColCoeffs(int ix, InsertIterator b) const {
200	200	CoinBigIndex begin = _prob->clpMatrix()->getVectorStarts()[ix];
201	201	CoinBigIndex end = begin + _prob->clpMatrix()->getVectorLengths()[ix];
202	202
203	203	const int* indices = _prob->clpMatrix()->getIndices();
204	204	const double* elements = _prob->clpMatrix()->getElements();
205	205
206	206	for (CoinBigIndex i = begin; i != end; ++i) {
207	207	*b = std::make_pair(indices[i], elements[i]);
208	208	++b;
209	209	}
210	210	}
211	211
212	212	void ClpLp::_setCoeff(int ix, int jx, Value value) {
213	213	_prob->modifyCoefficient(ix, jx, value);
214	214	}
215	215
216	216	ClpLp::Value ClpLp::_getCoeff(int ix, int jx) const {
217	217	CoinBigIndex begin = _prob->clpMatrix()->getVectorStarts()[ix];
218	218	CoinBigIndex end = begin + _prob->clpMatrix()->getVectorLengths()[ix];
219	219
220	220	const int* indices = _prob->clpMatrix()->getIndices();
221	221	const double* elements = _prob->clpMatrix()->getElements();
222	222
223	223	const int* it = std::lower_bound(indices + begin, indices + end, jx);
224	224	if (it != indices + end && *it == jx) {
225	225	return elements[it - indices];
226	226	} else {
227	227	return 0.0;
228	228	}
229	229	}
230	230
231	231	void ClpLp::_setColLowerBound(int i, Value lo) {
232	232	_prob->setColumnLower(i, lo == - INF ? - COIN_DBL_MAX : lo);
233	233	}
234	234
235	235	ClpLp::Value ClpLp::_getColLowerBound(int i) const {
236	236	double val = _prob->getColLower()[i];
237	237	return val == - COIN_DBL_MAX ? - INF : val;
238	238	}
239	239
240	240	void ClpLp::_setColUpperBound(int i, Value up) {
241	241	_prob->setColumnUpper(i, up == INF ? COIN_DBL_MAX : up);
242	242	}
243	243
244	244	ClpLp::Value ClpLp::_getColUpperBound(int i) const {
245	245	double val = _prob->getColUpper()[i];
246	246	return val == COIN_DBL_MAX ? INF : val;
247	247	}
248	248
249	249	void ClpLp::_setRowLowerBound(int i, Value lo) {
250	250	_prob->setRowLower(i, lo == - INF ? - COIN_DBL_MAX : lo);
251	251	}
252	252
253	253	ClpLp::Value ClpLp::_getRowLowerBound(int i) const {
254	254	double val = _prob->getRowLower()[i];
255	255	return val == - COIN_DBL_MAX ? - INF : val;
256	256	}