demo/lp_demo.cc
author deba
Mon, 03 Apr 2006 09:45:23 +0000
changeset 2031 080d51024ac5
parent 1875 98698b69a902
child 2369 6ae1a97055a2
permissions -rw-r--r--
Correcting the structure of the graph's and adaptor's map.
The template assign operators and map iterators can be used for adaptors also.

Some bugfix in the adaptors

New class SwapBpUGraphAdaptor which swaps the two nodeset of the graph.
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/* -*- C++ -*-
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 *
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 * This file is a part of LEMON, a generic C++ optimization library
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 *
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 * Copyright (C) 2003-2006
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 * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
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 * (Egervary Research Group on Combinatorial Optimization, EGRES).
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 *
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 * Permission to use, modify and distribute this software is granted
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 * provided that this copyright notice appears in all copies. For
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 * precise terms see the accompanying LICENSE file.
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 *
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 * This software is provided "AS IS" with no warranty of any kind,
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 * express or implied, and with no claim as to its suitability for any
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 * purpose.
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 *
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 */
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/// \ingroup demos
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/// \file
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/// \brief A program demonstrating the LEMON LP solver interface
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///
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/// This program is a simple application of the LEMON LP solver
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/// interface: we formulate a linear programming (LP) problem and then
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/// solve it using the underlying solver (GLPK or CPLEX for
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/// example). For the detailed documentation of the LEMON LP solver
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/// interface read \ref lemon::LpSolverBase "this".
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///
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/// \include lp_demo.cc
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#include <lemon/lp.h>
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#include <iostream>
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using namespace lemon;
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int main()
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{     
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 //The following example is taken from the documentation of the GLPK library.
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 //See it in the GLPK reference manual and among the GLPK sample files (sample.c)
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  //A default solver is taken
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  Lp lp;
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  typedef Lp::Row Row;
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  typedef Lp::Col Col;
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  std::cout<<"A program demonstrating the LEMON LP solver interface"<<std::endl; 
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  std::cout<<"Solver used: "<<default_solver_name<<std::endl;
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  //This will be a maximization
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  lp.max();
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  //We add coloumns (variables) to our problem
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  Col x1 = lp.addCol();
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  Col x2 = lp.addCol();
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  Col x3 = lp.addCol();
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  //Constraints
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  lp.addRow(x1+x2+x3 <=100);  
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  lp.addRow(10*x1+4*x2+5*x3<=600);  
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  lp.addRow(2*x1+2*x2+6*x3<=300);  
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  //Nonnegativity of the variables
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  lp.colLowerBound(x1, 0);
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  lp.colLowerBound(x2, 0);
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  lp.colLowerBound(x3, 0);
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  //Objective function
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  lp.setObj(10*x1+6*x2+4*x3);
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  //Call the routine of the underlying LP solver
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  lp.solve();
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  //Print results
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  if (lp.primalStatus()==LpSolverBase::OPTIMAL){
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    std::cout<<"Optimal solution found!"<<std::endl;
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    printf("optimum value = %g; x1 = %g; x2 = %g; x3 = %g\n", 
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	   lp.primalValue(), 
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	   lp.primal(x1), lp.primal(x2), lp.primal(x3));
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  }
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  else{
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    std::cout<<"Optimal solution not found!"<<std::endl;
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  }
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  //End of LEMON style code
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  //Here comes the same problem written in C using GLPK API routines
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//   LPX *lp;
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//       int ia[1+1000], ja[1+1000];
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//       double ar[1+1000], Z, x1, x2, x3;
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// s1:   lp = lpx_create_prob();
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// s2:   lpx_set_prob_name(lp, "sample");
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// s3:   lpx_set_obj_dir(lp, LPX_MAX);
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// s4:   lpx_add_rows(lp, 3);
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// s5:   lpx_set_row_name(lp, 1, "p");
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// s6:   lpx_set_row_bnds(lp, 1, LPX_UP, 0.0, 100.0);
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// s7:   lpx_set_row_name(lp, 2, "q");
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// s8:   lpx_set_row_bnds(lp, 2, LPX_UP, 0.0, 600.0);
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// s9:   lpx_set_row_name(lp, 3, "r");
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// s10:  lpx_set_row_bnds(lp, 3, LPX_UP, 0.0, 300.0);
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// s11:  lpx_add_cols(lp, 3);
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// s12:  lpx_set_col_name(lp, 1, "x1");
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// s13:  lpx_set_col_bnds(lp, 1, LPX_LO, 0.0, 0.0);
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// s14:  lpx_set_obj_coef(lp, 1, 10.0);
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// s15:  lpx_set_col_name(lp, 2, "x2");
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// s16:  lpx_set_col_bnds(lp, 2, LPX_LO, 0.0, 0.0);
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// s17:  lpx_set_obj_coef(lp, 2, 6.0);
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// s18:  lpx_set_col_name(lp, 3, "x3");
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// s19:  lpx_set_col_bnds(lp, 3, LPX_LO, 0.0, 0.0);
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// s20:  lpx_set_obj_coef(lp, 3, 4.0);
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// s21:  ia[1] = 1, ja[1] = 1, ar[1] =  1.0; /* a[1,1] =  1 */
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// s22:  ia[2] = 1, ja[2] = 2, ar[2] =  1.0; /* a[1,2] =  1 */
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// s23:  ia[3] = 1, ja[3] = 3, ar[3] =  1.0; /* a[1,3] =  1 */
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// s24:  ia[4] = 2, ja[4] = 1, ar[4] = 10.0; /* a[2,1] = 10 */
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// s25:  ia[5] = 3, ja[5] = 1, ar[5] =  2.0; /* a[3,1] =  2 */
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// s26:  ia[6] = 2, ja[6] = 2, ar[6] =  4.0; /* a[2,2] =  4 */
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// s27:  ia[7] = 3, ja[7] = 2, ar[7] =  2.0; /* a[3,2] =  2 */
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// s28:  ia[8] = 2, ja[8] = 3, ar[8] =  5.0; /* a[2,3] =  5 */
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// s29:  ia[9] = 3, ja[9] = 3, ar[9] =  6.0; /* a[3,3] =  6 */
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// s30:  lpx_load_matrix(lp, 9, ia, ja, ar);
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// s31:  lpx_simplex(lp);
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// s32:  Z = lpx_get_obj_val(lp);
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// s33:  x1 = lpx_get_col_prim(lp, 1);
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// s34:  x2 = lpx_get_col_prim(lp, 2);
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// s35:  x3 = lpx_get_col_prim(lp, 3);
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// s36:  printf("\nZ = %g; x1 = %g; x2 = %g; x3 = %g\n", Z, x1, x2, x3);
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// s37:  lpx_delete_prob(lp);
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//       return 0;
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  return 0;
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}