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// $Id: modify.cpp 1854 2013-01-28 00:02:55Z stefan $
// Copyright (C) 2007, International Business Machines
// Corporation and others. All Rights Reserved.
// This code is licensed under the terms of the Eclipse Public License (EPL).
/*
This example shows the creation of a model from arrays, solution
and then changes to objective and adding a row
*/
#include "CbcModel.hpp"
// Using as solver
#include "OsiClpSolverInterface.hpp"
int main (int argc, const char *argv[])
{
// model is as exmip1.mps from Data/samples
int numberRows=5;
int numberColumns=8;
int numberElements=14;
// matrix data - column ordered
CoinBigIndex start[9]={0,2,4,6,8,10,11,12,14};
int length[8]={2,2,2,2,2,1,1,2};
int rows[14]={0,4,0,1,1,2,0,3,0,4,2,3,0,4};
double elements[14]={3,5.6,1,2,1.1,1,-2,2.8,-1,1,1,-1.2,-1,1.9};
CoinPackedMatrix matrix(true,numberRows,numberColumns,numberElements,elements,rows,start,length);
// rim data
double objective[8]={1,0,0,0,2,0,0,-1};
double rowLower[5]={2.5,-COIN_DBL_MAX,4,1.8,3};
double rowUpper[5]={COIN_DBL_MAX,2.1,4,5,15};
double colLower[8]={2.5,0,0,0,0.5,0,0,0};
double colUpper[8]={COIN_DBL_MAX,4.1,1,1,4,COIN_DBL_MAX,COIN_DBL_MAX,4.3};
OsiClpSolverInterface solver1;
// load problem
solver1.loadProblem(matrix,colLower,colUpper,objective,
rowLower,rowUpper);
// mark integer
solver1.setInteger(2);
solver1.setInteger(3);
// Solve
solver1.initialSolve();
// Pass data and solver to CbcModel
CbcModel model(solver1);
// reduce printout
model.setLogLevel(1);
model.solver()->setHintParam(OsiDoReducePrint,true,OsiHintTry);
// Do complete search
model.branchAndBound();
/* Print solution. CbcModel clones solver so we
need to get current copy */
const double * solution = model.solver()->getColSolution();
int i;
for (i=0;i<numberColumns;i++) {
double value=solution[i];
if (fabs(value)>1.0e-7&&model.solver()->isInteger(i))
printf("i %d has value %g\n",i,value);
else if (fabs(value)>1.0e-7)
printf("c %d has value %g\n",i,value);
}
// Change objective
solver1.setObjCoeff(0,-100.0);
// Now model has too much information e.g. best solution
// simplest is to start again
// Pass data and solver to CbcModel
model = CbcModel(solver1);
// reduce printout
model.setLogLevel(1);
model.solver()->setHintParam(OsiDoReducePrint,true,OsiHintTry);
// Do complete search
model.branchAndBound();
solution = model.solver()->getColSolution();
for (i=0;i<numberColumns;i++) {
double value=solution[i];
if (fabs(value)>1.0e-7&&model.solver()->isInteger(i))
printf("i %d has value %g\n",i,value);
else if (fabs(value)>1.0e-7)
printf("c %d has value %g\n",i,value);
}
// Add constraint
int column[8]={0,1,2,3,4,5,6,7};
double element2[8] ={1,1,1,1,1,1,1,1};
solver1.addRow(8,column,element2,7.8,COIN_DBL_MAX);
// Now model has too much information e.g. best solution
// simplest is to start again
// Pass data and solver to CbcModel
model = CbcModel(solver1);
// reduce printout
model.setLogLevel(1);
model.solver()->setHintParam(OsiDoReducePrint,true,OsiHintTry);
// Do complete search
model.branchAndBound();
solution = model.solver()->getColSolution();
for (i=0;i<numberColumns;i++) {
double value=solution[i];
if (fabs(value)>1.0e-7&&model.solver()->isInteger(i))
printf("i %d has value %g\n",i,value);
else if (fabs(value)>1.0e-7)
printf("c %d has value %g\n",i,value);
}
return 0;
}
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