/*
* Java Genetic Algorithm Library (@__identifier__@).
* Copyright (c) @__year__@ Franz Wilhelmstötter
*
* 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.
*
* Author:
* Franz Wilhelmstötter (franz.wilhelmstoetter@gmx.at)
*/
package org.jenetics.example;
import static org.jenetics.engine.EvolutionResult.toBestPhenotype;
import static org.jenetics.engine.limit.bySteadyFitness;
import org.jenetics.BitChromosome;
import org.jenetics.BitGene;
import org.jenetics.Genotype;
import org.jenetics.Mutator;
import org.jenetics.Phenotype;
import org.jenetics.RouletteWheelSelector;
import org.jenetics.SinglePointCrossover;
import org.jenetics.engine.Engine;
import org.jenetics.engine.EvolutionStatistics;
public class OnesCounting {
// This method calculates the fitness for a given genotype.
private static Integer count(final Genotype<BitGene> gt) {
return ((BitChromosome)gt.getChromosome()).bitCount();
}
public static void main(String[] args) {
// Configure and build the evolution engine.
final Engine<BitGene, Integer> engine = Engine
.builder(
OnesCounting::count,
BitChromosome.of(20, 0.15))
.populationSize(500)
.selector(new RouletteWheelSelector<>())
.alterers(
new Mutator<>(0.55),
new SinglePointCrossover<>(0.06))
.build();
// Create evolution statistics consumer.
final EvolutionStatistics<Integer, ?>
statistics = EvolutionStatistics.ofNumber();
final Phenotype<BitGene, Integer> best = engine.stream()
// Truncate the evolution stream after 7 "steady"
// generations.
.limit(bySteadyFitness(7))
// The evolution will stop after maximal 100
// generations.
.limit(100)
// Update the evaluation statistics after
// each generation
.peek(statistics)
// Collect (reduce) the evolution stream to
// its best phenotype.
.collect(toBestPhenotype());
System.out.println(statistics);
System.out.println(best);
}
}