Try our new documentation site (beta).


/* Copyright 2016, Gurobi Optimization, Inc. */

/* 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;

main(int argc,
     char *argv[])
  if (argc < 2)
    cout << "Usage: feasopt_c++ filename" << endl;
    return 1;

  GRBEnv* env = 0;
  GRBConstr* c = 0;
    env = new GRBEnv();
    GRBModel feasmodel = GRBModel(*env, argv[1]);

    // Create a copy to use FeasRelax feature later */
    GRBModel feasmodel1 = GRBModel(feasmodel);

    // clear objective

    // 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_" +
      if (sense != '<')
        double coef = 1.0;
        feasmodel.addVar(0.0, GRB_INFINITY, 1.0, GRB_CONTINUOUS, 1,
                         &c[i], &coef, "ArtP_" +

    // optimize modified model

    // use FeasRelax feature */
    feasmodel1.feasRelax(GRB_FEASRELAX_LINEAR, true, false, true);
  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;

Try Gurobi for Free

Choose the evaluation license that fits you best, and start working with our Expert Team for technical guidance and support.

Evaluation License
Get a free, full-featured license of the Gurobi Optimizer to experience the performance, support, benchmarking and tuning services we provide as part of our product offering.
Academic License
Gurobi supports the teaching and use of optimization within academic institutions. We offer free, full-featured copies of Gurobi for use in class, and for research.
Cloud Trial

Request free trial hours, so you can see how quickly and easily a model can be solved on the cloud.