/*
* 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 java.util.Objects.requireNonNull;
import java.util.Random;
import java.util.function.Function;
import org.jenetics.EnumGene;
import org.jenetics.Mutator;
import org.jenetics.PartiallyMatchedCrossover;
import org.jenetics.Phenotype;
import org.jenetics.engine.Codec;
import org.jenetics.engine.Engine;
import org.jenetics.engine.EvolutionResult;
import org.jenetics.engine.Problem;
import org.jenetics.engine.codecs;
import org.jenetics.engine.limit;
import org.jenetics.util.ISeq;
import org.jenetics.util.LCG64ShiftRandom;
/**
* @author <a href="mailto:franz.wilhelmstoetter@gmx.at">Franz Wilhelmstötter</a>
* @version 3.4
* @since 3.4
*/
public class SubsetSum
implements Problem<ISeq<Integer>, EnumGene<Integer>, Integer>
{
private final ISeq<Integer> _basicSet;
private final int _size;
public SubsetSum(final ISeq<Integer> basicSet, final int size) {
_basicSet = requireNonNull(basicSet);
_size = size;
}
@Override
public Function<ISeq<Integer>, Integer> fitness() {
return subset -> Math.abs(
subset.stream()
.mapToInt(Integer::intValue)
.sum()
);
}
@Override
public Codec<ISeq<Integer>, EnumGene<Integer>> codec() {
return codecs.ofSubSet(_basicSet, _size);
}
public static SubsetSum of(final int n, final int k, final Random random) {
return new SubsetSum(
random.doubles()
.limit(n)
.mapToObj(d -> (int)((d - 0.5)*n))
.collect(ISeq.toISeq()),
k
);
}
public static void main(final String[] args) {
final SubsetSum problem = of(500, 15, new LCG64ShiftRandom(101010));
final Engine<EnumGene<Integer>, Integer> engine = Engine.builder(problem)
.minimizing()
.maximalPhenotypeAge(5)
.alterers(
new PartiallyMatchedCrossover<>(0.4),
new Mutator<>(0.3))
.build();
final Phenotype<EnumGene<Integer>, Integer> result = engine.stream()
.limit(limit.bySteadyFitness(55))
.collect(EvolutionResult.toBestPhenotype());
System.out.print(result);
}
}