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dense_c.c
/* Copyright 2020, Gurobi Optimization, LLC */
/* This example formulates and solves the following simple QP model:
minimize x + y + x^2 + x*y + y^2 + y*z + z^2
subject to x + 2 y + 3 z >= 4
x + y >= 1
x, y, z non-negative
The example illustrates the use of dense matrices to store A and Q
(and dense vectors for the other relevant data). We don't recommend
that you use dense matrices, but this example may be helpful if you
already have your data in this format.
*/
#include <stdlib.h>
#include <stdio.h>
#include "gurobi_c.h"
/*
Solve an LP/QP/MILP/MIQP represented using dense matrices. This
routine assumes that A and Q are both stored in row-major order.
It returns 1 if the optimization succeeds. When successful,
it returns the optimal objective value in 'objvalP', and the
optimal solution vector in 'solution'.
*/
static int
dense_optimize(GRBenv *env,
int rows,
int cols,
double *c, /* linear portion of objective function */
double *Q, /* quadratic portion of objective function */
double *A, /* constraint matrix */
char *sense, /* constraint senses */
double *rhs, /* RHS vector */
double *lb, /* variable lower bounds */
double *ub, /* variable upper bounds */
char *vtype, /* variable types (continuous, binary, etc.) */
double *solution,
double *objvalP)
{
GRBmodel *model = NULL;
int i, j, optimstatus;
int error = 0;
int success = 0;
/* Create an empty model */
error = GRBnewmodel(env, &model, "dense", cols, c, lb, ub, vtype, NULL);
if (error) goto QUIT;
error = GRBaddconstrs(model, rows, 0, NULL, NULL, NULL, sense, rhs, NULL);
if (error) goto QUIT;
/* Populate A matrix */
for (i = 0; i < rows; i++) {
for (j = 0; j < cols; j++) {
if (A[i*cols+j] != 0) {
error = GRBchgcoeffs(model, 1, &i, &j, &A[i*cols+j]);
if (error) goto QUIT;
}
}
}
/* Populate Q matrix */
if (Q) {
for (i = 0; i < cols; i++) {
for (j = 0; j < cols; j++) {
if (Q[i*cols+j] != 0) {
error = GRBaddqpterms(model, 1, &i, &j, &Q[i*cols+j]);
if (error) goto QUIT;
}
}
}
}
/* Optimize model */
error = GRBoptimize(model);
if (error) goto QUIT;
/* Write model to 'dense.lp' */
error = GRBwrite(model, "dense.lp");
if (error) goto QUIT;
/* Capture solution information */
error = GRBgetintattr(model, GRB_INT_ATTR_STATUS, &optimstatus);
if (error) goto QUIT;
if (optimstatus == GRB_OPTIMAL) {
error = GRBgetdblattr(model, GRB_DBL_ATTR_OBJVAL, objvalP);
if (error) goto QUIT;
error = GRBgetdblattrarray(model, GRB_DBL_ATTR_X, 0, cols, solution);
if (error) goto QUIT;
success = 1;
}
QUIT:
/* Error reporting */
if (error) {
printf("ERROR: %s\n", GRBgeterrormsg(env));
exit(1);
}
/* Free model */
GRBfreemodel(model);
return success;
}
int
main(int argc,
char *argv[])
{
GRBenv *env = NULL;
int error = 0;
double c[] = {1, 1, 0};
double Q[3][3] = {{1, 1, 0}, {0, 1, 1}, {0, 0, 1}};
double A[2][3] = {{1, 2, 3}, {1, 1, 0}};
char sense[] = {'>', '>'};
double rhs[] = {4, 1};
double lb[] = {0, 0, 0};
double sol[3];
int solved;
double objval;
/* Create environment */
error = GRBloadenv(&env, "dense.log");
if (error) goto QUIT;
/* Solve the model */
solved = dense_optimize(env, 2, 3, c, &Q[0][0], &A[0][0], sense, rhs, lb,
NULL, NULL, sol, &objval);
if (solved)
printf("Solved: x=%.4f, y=%.4f, z=%.4f\n", sol[0], sol[1], sol[2]);
QUIT:
/* Free environment */
GRBfreeenv(env);
return 0;
}
