| 1 | package de.uka.ipd.sdq.dsexplore.opt4j.operator; |
| 2 | |
| 3 | import org.opt4j.common.random.Rand; |
| 4 | import org.opt4j.operator.crossover.Crossover; |
| 5 | import org.opt4j.optimizer.ea.Pair; |
| 6 | |
| 7 | import com.google.inject.Inject; |
| 8 | |
| 9 | import de.uka.ipd.sdq.dsexplore.opt4j.genotype.DesignDecisionGenotype; |
| 10 | |
| 11 | /** |
| 12 | * Uniform crossover implementation. For each gene of the first offspring, |
| 13 | * it is randomly decided whether the value of parent 1 or parent 2 is taken. |
| 14 | * The second offspring then is the opposite. |
| 15 | * |
| 16 | * @author martens |
| 17 | * |
| 18 | */ |
| 19 | public class UniformDesignDecisionGenotypeCrossover implements Crossover<DesignDecisionGenotype> { |
| 20 | |
| 21 | private Rand random; |
| 22 | |
| 23 | @Inject |
| 24 | public UniformDesignDecisionGenotypeCrossover(Rand random) { |
| 25 | this.random = random; |
| 26 | } |
| 27 | |
| 28 | @Override |
| 29 | public Pair<DesignDecisionGenotype> crossover(DesignDecisionGenotype parent1, DesignDecisionGenotype parent2) { |
| 30 | |
| 31 | DesignDecisionGenotype o1 = parent1.newInstance(); |
| 32 | DesignDecisionGenotype o2 = parent2.newInstance(); |
| 33 | |
| 34 | if (o1.size() != o2.size()){ |
| 35 | throw new RuntimeException("Two genomes do not have the same length: "+parent1 + " and "+parent2); |
| 36 | } |
| 37 | |
| 38 | for (int i = 0; i < o2.size(); i ++) { |
| 39 | if (this.random.nextBoolean()){ |
| 40 | o1.add(parent1.get(i)); |
| 41 | o2.add(parent2.get(i)); |
| 42 | } else { |
| 43 | o1.add(parent2.get(i)); |
| 44 | o2.add(parent1.get(i)); |
| 45 | } |
| 46 | } |
| 47 | |
| 48 | Pair<DesignDecisionGenotype> offspring = new Pair<DesignDecisionGenotype>(o1, o2); |
| 49 | return offspring; |
| 50 | } |
| 51 | |
| 52 | } |