Try our new documentation site (beta).

Filter Content By
Version

### gc_funcnonlinear_c.c

/* Copyright 2024, Gurobi Optimization, LLC

This example considers the following nonconvex nonlinear problem

minimize   sin(x) + cos(2*x) + 1
subject to  0.25*exp(x) - x <= 0
-1 <= x <= 4

We show you two approaches to solve it as a nonlinear model:

1) Set the paramter FuncNonlinear = 1 to handle all general function
constraints as true nonlinear functions.

2) Set the attribute FuncNonlinear = 1 for each general function
constraint to handle these as true nonlinear functions.

*/

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

static int
printsol(GRBmodel *m)
{
double x[1];
double vio;
int    error = 0;

error = GRBgetdblattrarray(m, "X", 0, 1, x);
if (error) goto QUIT;

printf("x = %g", x[0]);

QUIT:

return error;
}

int
main(int   argc,
char *argv[])
{
GRBenv   *env     = NULL;
GRBmodel *model   = NULL;
int       error   = 0;
int       attrs[] = {1, 1, 1};
int       ind[2];
double    val[2];

/* Create environment */

error = GRBloadenv(&env, NULL);
if (error) goto QUIT;

/* Create a new model */

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

/* Add variables */

error = GRBaddvar(model, 0, NULL, NULL, 0.0, -1.0, 4.0, GRB_CONTINUOUS, "x");
if (error) goto QUIT;
error = GRBaddvar(model, 0, NULL, NULL, 0.0, -2.0, 8.0, GRB_CONTINUOUS, "twox");
if (error) goto QUIT;
error = GRBaddvar(model, 0, NULL, NULL, 0.0, -1.0, 1.0, GRB_CONTINUOUS, "sinx");
if (error) goto QUIT;
error = GRBaddvar(model, 0, NULL, NULL, 0.0, -1.0, 1.0, GRB_CONTINUOUS, "cos2x");
if (error) goto QUIT;
error = GRBaddvar(model, 0, NULL, NULL, 0.0, 0.0, GRB_INFINITY, GRB_CONTINUOUS, "expx");
if (error) goto QUIT;

/* Add constant term to objective */

error = GRBsetdblattr(model, "ObjCon", 1.0);

/* Add linear constraint: 0.25*expx - x <= 0 */
ind[0] = 4; ind[1] = 0;
val[0] = 0.25; val[1] = -1.0;

error = GRBaddconstr(model, 2, ind, val, GRB_LESS_EQUAL, 0.0, "c1");
if (error) goto QUIT;

/* Add linear constraint: 2*x - twox = 0 */
ind[0] = 0; ind[1] = 1;
val[0] = 2; val[1] = -1.0;

error = GRBaddconstr(model, 2, ind, val, GRB_EQUAL, 0.0, "c2");
if (error) goto QUIT;

/* Add general function constraint: sinx = sin(x) */
error = GRBaddgenconstrSin(model, "gcf1", 0, 2, NULL);
if (error) goto QUIT;

/* Add general function constraint: cos2x = cos(twox) */
error = GRBaddgenconstrCos(model, "gcf2", 1, 3, NULL);
if (error) goto QUIT;

/* Add general function constraint: expx = exp(x) */
error = GRBaddgenconstrExp(model, "gcf3", 0, 4, NULL);
if (error) goto QUIT;

/* Approach 1) Set FuncNonlinear parameter */

error = GRBsetintparam(GRBgetenv(model), "FuncNonlinear", 1);
if (error) goto QUIT;

/* Optimize the model and print solution */

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

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

/* Restore unsolved state */
error = GRBresetmodel(model);
if (error) goto QUIT;

/* Set FuncNonlinear parater back to its default value */
error = GRBsetintparam(GRBgetenv(model), "FuncNonlinear", 0);
if (error) goto QUIT;

/* Approach 2) Set FuncNonlinear attribute for every
general function constraint */

error = GRBsetintattrarray(model, "FuncNonlinear", 0, 3, attrs);
if (error) goto QUIT;

/* Optimize the model and print solution */

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

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

QUIT:

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

/* Free model */

GRBfreemodel(model);

/* Free environment */

GRBfreeenv(env);

return 0;
}

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

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.
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.