org.evosuite.ga.metaheuristics.mulambda.AbstractMuLambda Maven / Gradle / Ivy

Go to download
Show more of this group Show more artifacts with this name
Show all versions of evosuite-client Show documentation
The newest version!
/**
 * Copyright (C) 2010-2018 Gordon Fraser, Andrea Arcuri and EvoSuite
 * contributors
 *
 * This file is part of EvoSuite.
 *
 * EvoSuite 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 3.0 of the License, or
 * (at your option) any later version.
 *
 * EvoSuite 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 Public License for more details.
 *
 * You should have received a copy of the GNU Lesser General Public
 * License along with EvoSuite. If not, see .
 */
package org.evosuite.ga.metaheuristics.mulambda;

import org.evosuite.Properties;
import org.evosuite.TimeController;
import org.evosuite.ga.Chromosome;
import org.evosuite.ga.ChromosomeFactory;
import org.evosuite.ga.metaheuristics.GeneticAlgorithm;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

/**
 * AbstractMuLambda
 *
 * @author José Campos
 */
public abstract class AbstractMuLambda extends GeneticAlgorithm {

  private static final long serialVersionUID = 2738004761503761376L;

  private static final Logger logger = LoggerFactory.getLogger(AbstractMuLambda.class);

  protected final int mu;

  protected final int lambda;

  public AbstractMuLambda(ChromosomeFactory factory, int mu, int lambda) {
    super(factory);
    this.mu = mu;
    this.lambda = lambda;
  }

  /** {@inheritDoc} */
  @Override
  public void initializePopulation() {
    this.notifySearchStarted();
    this.currentIteration = 0;

    // set up initial population
    this.generateRandomPopulation(this.mu);
    assert this.population.size() == this.mu;

    // update fitness values of all individuals
    this.calculateFitnessAndSortPopulation();

    this.notifyIteration();
  }

  /** {@inheritDoc} */
  @Override
  public void generateSolution() {
    if (this.population.isEmpty()) {
      this.initializePopulation();
    }

    if (Properties.ENABLE_SECONDARY_OBJECTIVE_AFTER > 0
        || Properties.ENABLE_SECONDARY_OBJECTIVE_STARVATION) {
      this.disableFirstSecondaryCriterion();
    }

    int starvationCounter = 0;
    double bestFitness = Double.MAX_VALUE;
    double lastBestFitness = Double.MAX_VALUE;

    if (getFitnessFunction().isMaximizationFunction()) {
      bestFitness = 0.0;
      lastBestFitness = 0.0;
    }

    while (!isFinished()) {
      logger.debug("Current population: " + getAge() + "/" + Properties.SEARCH_BUDGET);
      logger.info("Best fitness: " + getBestIndividual().getFitness());
      this.evolve();

      this.applyLocalSearch();

      double newFitness = getBestIndividual().getFitness();
      if (getFitnessFunction().isMaximizationFunction()) {
        assert (newFitness >= bestFitness) : "best fitness was: " + bestFitness
            + ", now best fitness is " + newFitness;
      } else {
        assert (newFitness <= bestFitness) : "best fitness was: " + bestFitness
            + ", now best fitness is " + newFitness;
      }
      bestFitness = newFitness;

      if (Double.compare(bestFitness, lastBestFitness) == 0) {
        starvationCounter++;
      } else {
        logger.info("reset starvationCounter after " + starvationCounter + " iterations");
        starvationCounter = 0;
        lastBestFitness = bestFitness;
      }

      // update fitness values of all individuals
      this.updateFitnessFunctionsAndValues();

      this.notifyIteration();
    }

    TimeController.execute(this::updateBestIndividualFromArchive, "update from archive", 5_000);
    this.notifySearchFinished();
  }
}