// Copyright 2010-2018 Google LLC // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. // Minimal example to call the MIP solver. // [START program] package com.google.ortools.examples; // [START import] import com.google.ortools.linearsolver.MPConstraint; import com.google.ortools.linearsolver.MPObjective; import com.google.ortools.linearsolver.MPSolver; import com.google.ortools.linearsolver.MPVariable; // [END import] /** Minimal Mixed Integer Programming example to showcase calling the solver. */ public class SimpleMipProgram { static { System.loadLibrary("jniortools"); } public static void main(String[] args) throws Exception { // [START solver] // Create the linear solver with the CBC backend. MPSolver solver = MPSolver.createSolver("SimpleMipProgram", "CBC"); // [END solver] // [START variables] double infinity = java.lang.Double.POSITIVE_INFINITY; // x and y are integer non-negative variables. MPVariable x = solver.makeIntVar(0.0, infinity, "x"); MPVariable y = solver.makeIntVar(0.0, infinity, "y"); System.out.println("Number of variables = " + solver.numVariables()); // [END variables] // [START constraints] // x + 7 * y <= 17.5. MPConstraint c0 = solver.makeConstraint(-infinity, 17.5, "c0"); c0.setCoefficient(x, 1); c0.setCoefficient(y, 7); // x <= 3.5. MPConstraint c1 = solver.makeConstraint(-infinity, 3.5, "c1"); c1.setCoefficient(x, 1); c1.setCoefficient(y, 0); System.out.println("Number of constraints = " + solver.numConstraints()); // [END constraints] // [START objective] // Maximize x + 10 * y. MPObjective objective = solver.objective(); objective.setCoefficient(x, 1); objective.setCoefficient(y, 10); objective.setMaximization(); // [END objective] // [START solve] final MPSolver.ResultStatus resultStatus = solver.solve(); // [END solve] // [START print_solution] if (resultStatus == MPSolver.ResultStatus.OPTIMAL) { System.out.println("Solution:"); System.out.println("Objective value = " + objective.value()); System.out.println("x = " + x.solutionValue()); System.out.println("y = " + y.solutionValue()); // [END print_solution] // [START advanced] System.out.println("\nAdvanced usage:"); System.out.println("Problem solved in " + solver.wallTime() + " milliseconds"); System.out.println("Problem solved in " + solver.iterations() + " iterations"); System.out.println("Problem solved in " + solver.nodes() + " branch-and-bound nodes"); // [END advanced] } else { System.err.println("The problem does not have an optimal solution!"); } } } // [END program]