demo/lp_demo.cc
author deba
Tue, 10 Jun 2008 11:36:17 +0000
changeset 2612 3d65053d01a3
parent 2391 14a343be7a5a
permissions -rw-r--r--
Bug fix initialization
The std::numeric_limits<double>::min() means the smallest positive number,
and not the smallest number in the whole range of double.
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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) 2003-2008
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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.obj(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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}