org.chocosolver.samples.integer.SMPTSP Maven / Gradle / Ivy

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/**
 * Copyright (c) 2015, Ecole des Mines de Nantes
 * All rights reserved.
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 *    derived from this software without specific prior written permission.
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 * THIS SOFTWARE IS PROVIDED BY  ''AS IS'' AND ANY
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package org.chocosolver.samples.integer;

import org.chocosolver.samples.AbstractProblem;
import org.chocosolver.solver.ResolutionPolicy;
import org.chocosolver.solver.Solver;
import org.chocosolver.solver.constraints.ICF;
import org.chocosolver.solver.search.loop.monitors.IMonitorInitialize;
import org.chocosolver.solver.search.loop.monitors.IMonitorSolution;
import org.chocosolver.solver.search.solution.Solution;
import org.chocosolver.solver.search.strategy.ISF;
import org.chocosolver.solver.variables.IntVar;
import org.chocosolver.solver.variables.VF;

/**
 * simple CP model to solve a toy SMPTSP instance
 * (see Fages and Lapègue, CP'13 or Artificial Intelligence journal)
 * Enumeration of all optimal solutions
 *
 * @since 01/01/2014
 * @author Jean-Guillaume Fages
 */
public class SMPTSP extends AbstractProblem {

	// ***********************************************************************************
	// VARIABLES
	// ***********************************************************************************

	//input
	private int nbTasks;
	private int nbAvailableShifts;
	private int bestObj;

	// model
	private IntVar nbValues;
	private IntVar[] assignment;

	// ***********************************************************************************
	// METHODS
	// ***********************************************************************************

	@Override
	public void createSolver() {
		solver = new Solver("Shift Minimization Personnel Task Scheduling Problem");
	}

	@Override
	public void buildModel() {
		// Input
		nbTasks = 5;
		nbAvailableShifts = 5;
		int[][] skilledShifts = new int[][]{{2,3,4}, {1,2,3}, {1,3}, {3,4,5}, {1,2,5}};
		final boolean[][] taskOverlaps = new boolean[][]{
				{true, true, true, true, false},
				{true, true, true, false, false},
				{true, true, true, true, false},
				{true, false, true, true, true},
				{false, false, false, true, true},
		};

		// Variables
		nbValues = VF.bounded("nb shifts", 0, nbAvailableShifts, solver);
		assignment = new IntVar[nbTasks];
		for(int i=0;i {
            bestObj = nbValues.getValue();
            System.out.println("Solution found! Objective = "+bestObj);
        });
	}

	@Override
	public void solve() {
		solver.findAllOptimalSolutions(ResolutionPolicy.MINIMIZE, nbValues, false);
	}

	@Override
	public void prettyOut() {
		int nb = 1;
		for(Solution s:solver.getSolutionRecorder().getSolutions()){
			System.out.println("Optimal solution : "+nb);
			for(int i=0;i<5;i++){
				System.out.println(assignment[i].getName()+" = "+s.getIntVal(assignment[i]));
			}nb++;
		}
	}

	public static void main(String[] args){
	    new SMPTSP().execute(args);
	}
}