\( \newcommand{\E}{\mathrm{E}} \) \( \newcommand{\A}{\mathrm{A}} \) \( \newcommand{\R}{\mathrm{R}} \) \( \newcommand{\N}{\mathrm{N}} \) \( \newcommand{\Q}{\mathrm{Q}} \) \( \newcommand{\Z}{\mathrm{Z}} \) \( \def\ccSum #1#2#3{ \sum_{#1}^{#2}{#3} } \def\ccProd #1#2#3{ \sum_{#1}^{#2}{#3} }\)

CGAL 4.8 - Linear and Quadratic Programming Solver

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QP_solver/cycling.cpp
// example: solve a linear program that by default leads to cycling,
// using Bland pricing
#include <iostream>
#include <fstream>
#include <CGAL/basic.h>
#include <CGAL/QP_models.h>
#include <CGAL/QP_functions.h>
// choose exact floating-point type
#ifdef CGAL_USE_GMP
#include <CGAL/Gmpzf.h>
typedef CGAL::Gmpzf ET;
#else
#include <CGAL/MP_Float.h>
typedef CGAL::MP_Float ET;
#endif
// program and solution types
typedef CGAL::Quadratic_program_from_mps<double> Program;
typedef CGAL::Quadratic_program_solution<ET> Solution;
int main() {
std::ifstream in ("cycling.mps");
Program lp(in); // read program from file
assert (lp.is_valid()); // we should have a valid mps file...
assert (lp.is_linear()); // ... and it should be linear...
assert (lp.is_nonnegative()); // as well as nonnegative
// solve the program, using ET as the exact type
// choose verbose mode and Bland pricing
CGAL::Quadratic_program_options options;
options.set_verbosity(1); // verbose mode
options.set_pricing_strategy(CGAL::QP_BLAND); // Bland's rule
options.set_auto_validation(true); // automatic self-check
Solution s = CGAL::solve_nonnegative_linear_program(lp, ET(), options);
assert (s.is_valid()); // did the self-check succeed?
// output solution
std::cout << s;
return 0;
}