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//  This program is free software: you can redistribute it and/or modify
//  it under the terms of the GNU Lesser General Public License as published by
//  the Free Software Foundation, either version 3 of the License, or
//  (at your option) any later version.
//
//  This program is distributed in the hope that it will be useful,
//  but WITHOUT ANY WARRANTY; without even the implied warranty of
//  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
//  GNU Lesser General Public License for more details.
// 
//  You should have received a copy of the GNU Lesser General Public License
//  along with this program.  If not, see .

package org.uma.jmetal.runner.singleobjective;

import org.uma.jmetal.algorithm.Algorithm;
import org.uma.jmetal.algorithm.singleobjective.geneticalgorithm.GeneticAlgorithmBuilder;
import org.uma.jmetal.operator.CrossoverOperator;
import org.uma.jmetal.operator.MutationOperator;
import org.uma.jmetal.operator.SelectionOperator;
import org.uma.jmetal.operator.impl.crossover.PMXCrossover;
import org.uma.jmetal.operator.impl.mutation.PermutationSwapMutation;
import org.uma.jmetal.operator.impl.selection.BinaryTournamentSelection;
import org.uma.jmetal.problem.PermutationProblem;
import org.uma.jmetal.problem.singleobjective.TSP;
import org.uma.jmetal.solution.PermutationSolution;
import org.uma.jmetal.util.AlgorithmRunner;
import org.uma.jmetal.util.JMetalLogger;
import org.uma.jmetal.util.comparator.RankingAndCrowdingDistanceComparator;
import org.uma.jmetal.util.fileoutput.SolutionSetOutput;
import org.uma.jmetal.util.fileoutput.impl.DefaultFileOutputContext;

import java.util.ArrayList;
import java.util.List;

/**
 * Class to configure and run a generational genetic algorithm. The target problem is OneMax.
 *
 * @author Antonio J. Nebro 
 */
public class GenerationalGeneticAlgorithmTSPRunner {
  /**
   * Usage: java org.uma.jmetal.runner.singleobjective.GenerationalGeneticAlgorithmRunner
   */
  public static void main(String[] args) throws Exception {
    PermutationProblem> problem;
    Algorithm> algorithm;
    CrossoverOperator> crossover;
    MutationOperator> mutation;
    SelectionOperator>, PermutationSolution> selection;

    problem = new TSP("/tspInstances/kroA100.tsp");

    crossover = new PMXCrossover(0.9) ;

    double mutationProbability = 1.0 / problem.getNumberOfVariables() ;
    mutation = new PermutationSwapMutation(mutationProbability) ;

    selection = new BinaryTournamentSelection>(new RankingAndCrowdingDistanceComparator>());

    algorithm = new GeneticAlgorithmBuilder<>(problem, crossover, mutation)
            .setPopulationSize(100)
            .setMaxEvaluations(250000)
            .setSelectionOperator(selection)
            .build() ;

    AlgorithmRunner algorithmRunner = new AlgorithmRunner.Executor(algorithm)
            .execute() ;

    PermutationSolution solution = algorithm.getResult() ;
    List> population = new ArrayList<>(1) ;
    population.add(solution) ;

    long computingTime = algorithmRunner.getComputingTime() ;

    new SolutionSetOutput.Printer(population)
            .setSeparator("\t")
            .setVarFileOutputContext(new DefaultFileOutputContext("VAR.tsv"))
            .setFunFileOutputContext(new DefaultFileOutputContext("FUN.tsv"))
            .print();

    JMetalLogger.logger.info("Total execution time: " + computingTime + "ms");
    JMetalLogger.logger.info("Objectives values have been written to file FUN.tsv");
    JMetalLogger.logger.info("Variables values have been written to file VAR.tsv");

  }
}