Try our new documentation site.


qp_c.c


/* Copyright 2020, Gurobi Optimization, LLC */

/* This example formulates and solves the following simple QP model:

     minimize    x^2 + x*y + y^2 + y*z + z^2 + 2 x
     subject to  x + 2 y + 3 z >= 4
                 x +   y       >= 1
                 x, y, z non-negative

   It solves it once as a continuous model, and once as an integer model.
*/

#include <stdlib.h>
#include <stdio.h>
#include "gurobi_c.h"

int
main(int   argc,
     char *argv[])
{
  GRBenv   *env   = NULL;
  GRBmodel *model = NULL;
  int       error = 0;
  double    sol[3];
  int       ind[3];
  double    val[3];
  int       qrow[5];
  int       qcol[5];
  double    qval[5];
  char      vtype[3];
  int       optimstatus;
  double    objval;

  /* Create environment */

  error = GRBloadenv(&env, "qp.log");
  if (error) goto QUIT;

  /* Create an empty model */

  error = GRBnewmodel(env, &model, "qp", 0, NULL, NULL, NULL, NULL, NULL);
  if (error) goto QUIT;

  /* Add variables */

  error = GRBaddvars(model, 3, 0, NULL, NULL, NULL, NULL, NULL, NULL, NULL,
                     NULL);
  if (error) goto QUIT;

  /* Quadratic objective terms */

  qrow[0] = 0; qrow[1] = 0; qrow[2] = 1; qrow[3] = 1; qrow[4] = 2;
  qcol[0] = 0; qcol[1] = 1; qcol[2] = 1; qcol[3] = 2; qcol[4] = 2;
  qval[0] = 1; qval[1] = 1; qval[2] = 1; qval[3] = 1; qval[4] = 1;

  error = GRBaddqpterms(model, 5, qrow, qcol, qval);
  if (error) goto QUIT;

  /* Linear objective term */

  error = GRBsetdblattrelement(model, GRB_DBL_ATTR_OBJ, 0, 2.0);
  if (error) goto QUIT;

  /* First constraint: x + 2 y + 3 z <= 4 */

  ind[0] = 0; ind[1] = 1; ind[2] = 2;
  val[0] = 1; val[1] = 2; val[2] = 3;

  error = GRBaddconstr(model, 3, ind, val, GRB_GREATER_EQUAL, 4.0, "c0");
  if (error) goto QUIT;

  /* Second constraint: x + y >= 1 */

  ind[0] = 0; ind[1] = 1;
  val[0] = 1; val[1] = 1;

  error = GRBaddconstr(model, 2, ind, val, GRB_GREATER_EQUAL, 1.0, "c1");
  if (error) goto QUIT;

  /* Optimize model */

  error = GRBoptimize(model);
  if (error) goto QUIT;

  /* Write model to 'qp.lp' */

  error = GRBwrite(model, "qp.lp");
  if (error) goto QUIT;

  /* Capture solution information */

  error = GRBgetintattr(model, GRB_INT_ATTR_STATUS, &optimstatus);
  if (error) goto QUIT;

  error = GRBgetdblattr(model, GRB_DBL_ATTR_OBJVAL, &objval);
  if (error) goto QUIT;

  error = GRBgetdblattrarray(model, GRB_DBL_ATTR_X, 0, 3, sol);
  if (error) goto QUIT;

  printf("\nOptimization complete\n");
  if (optimstatus == GRB_OPTIMAL) {
    printf("Optimal objective: %.4e\n", objval);

    printf("  x=%.4f, y=%.4f, z=%.4f\n", sol[0], sol[1], sol[2]);
  } else if (optimstatus == GRB_INF_OR_UNBD) {
    printf("Model is infeasible or unbounded\n");
  } else {
    printf("Optimization was stopped early\n");
  }


  /* Modify variable types */

  vtype[0] = GRB_INTEGER; vtype[1] = GRB_INTEGER; vtype[2] = GRB_INTEGER;

  error = GRBsetcharattrarray(model, GRB_CHAR_ATTR_VTYPE, 0, 3, vtype);
  if (error) goto QUIT;

  /* Optimize model */

  error = GRBoptimize(model);
  if (error) goto QUIT;

  /* Write model to 'qp2.lp' */

  error = GRBwrite(model, "qp2.lp");
  if (error) goto QUIT;

  /* Capture solution information */

  error = GRBgetintattr(model, GRB_INT_ATTR_STATUS, &optimstatus);
  if (error) goto QUIT;

  error = GRBgetdblattr(model, GRB_DBL_ATTR_OBJVAL, &objval);
  if (error) goto QUIT;

  error = GRBgetdblattrarray(model, GRB_DBL_ATTR_X, 0, 3, sol);
  if (error) goto QUIT;

  printf("\nOptimization complete\n");
  if (optimstatus == GRB_OPTIMAL) {
    printf("Optimal objective: %.4e\n", objval);

    printf("  x=%.4f, y=%.4f, z=%.4f\n", sol[0], sol[1], sol[2]);
  } else if (optimstatus == GRB_INF_OR_UNBD) {
    printf("Model is infeasible or unbounded\n");
  } else {
    printf("Optimization was stopped early\n");
  }

QUIT:

  /* Error reporting */

  if (error) {
    printf("ERROR: %s\n", GRBgeterrormsg(env));
    exit(1);
  }

  /* Free model */

  GRBfreemodel(model);

  /* Free environment */

  GRBfreeenv(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.

Search