/* Copyright 2024, Gurobi Optimization, LLC */
/* This example reads a MIP model from a file, adds artificial
variables to each constraint, and then minimizes the sum of the
artificial variables. A solution with objective zero corresponds
to a feasible solution to the input model.
We can also use FeasRelax feature to do it. In this example, we
use minrelax=1, i.e. optimizing the returned model finds a solution
that minimizes the original objective, but only from among those
solutions that minimize the sum of the artificial variables. */
#include "gurobi_c++.h"
using namespace std;
int
main(int argc,
char *argv[])
{
if (argc < 2)
{
cout << "Usage: feasopt_c++ filename" << endl;
return 1;
}
GRBEnv* env = 0;
GRBConstr* c = 0;
try
{
env = new GRBEnv();
GRBModel feasmodel = GRBModel(*env, argv[1]);
// Create a copy to use FeasRelax feature later */
GRBModel feasmodel1 = GRBModel(feasmodel);
// clear objective
feasmodel.setObjective(GRBLinExpr(0.0));
// add slack variables
c = feasmodel.getConstrs();
for (int i = 0; i < feasmodel.get(GRB_IntAttr_NumConstrs); ++i)
{
char sense = c[i].get(GRB_CharAttr_Sense);
if (sense != '>')
{
double coef = -1.0;
feasmodel.addVar(0.0, GRB_INFINITY, 1.0, GRB_CONTINUOUS, 1,
&c[i], &coef, "ArtN_" +
c[i].get(GRB_StringAttr_ConstrName));
}
if (sense != '<')
{
double coef = 1.0;
feasmodel.addVar(0.0, GRB_INFINITY, 1.0, GRB_CONTINUOUS, 1,
&c[i], &coef, "ArtP_" +
c[i].get(GRB_StringAttr_ConstrName));
}
}
// optimize modified model
feasmodel.optimize();
feasmodel.write("feasopt.lp");
// use FeasRelax feature */
feasmodel1.feasRelax(GRB_FEASRELAX_LINEAR, true, false, true);
feasmodel1.write("feasopt1.lp");
feasmodel1.optimize();
}
catch (GRBException e)
{
cout << "Error code = " << e.getErrorCode() << endl;
cout << e.getMessage() << endl;
}
catch (...)
{
cout << "Error during optimization" << endl;
}
delete[] c;
delete env;
return 0;
}