org.apache.commons.math3.genetics.CycleCrossover Maven / Gradle / Ivy
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* (the "License"); you may not use this file except in compliance with
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*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
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* See the License for the specific language governing permissions and
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package org.apache.commons.math3.genetics;
import java.util.ArrayList;
import java.util.HashSet;
import java.util.List;
import java.util.Set;
import org.apache.commons.math3.exception.DimensionMismatchException;
import org.apache.commons.math3.exception.MathIllegalArgumentException;
import org.apache.commons.math3.exception.util.LocalizedFormats;
/**
* Cycle Crossover [CX] builds offspring from ordered chromosomes by identifying cycles
* between two parent chromosomes. To form the children, the cycles are copied from the
* respective parents.
*
* To form a cycle the following procedure is applied:
*
* - start with the first gene of parent 1
* - look at the gene at the same position of parent 2
* - go to the position with the same gene in parent 1
* - add this gene index to the cycle
* - repeat the steps 2-5 until we arrive at the starting gene of this cycle
*
* The indices that form a cycle are then used to form the children in alternating order, i.e.
* in cycle 1, the genes of parent 1 are copied to child 1, while in cycle 2 the genes of parent 1
* are copied to child 2, and so forth ...
*
*
* Example (zero-start cycle):
*
* p1 = (8 4 7 3 6 2 5 1 9 0) X c1 = (8 1 2 3 4 5 6 7 9 0)
* p2 = (0 1 2 3 4 5 6 7 8 9) X c2 = (0 4 7 3 6 2 5 1 8 9)
*
* cycle 1: 8 0 9
* cycle 2: 4 1 7 2 5 6
* cycle 3: 3
*
*
* This policy works only on {@link AbstractListChromosome}, and therefore it
* is parameterized by T. Moreover, the chromosomes must have same lengths.
*
* @see
* Cycle Crossover Operator
*
* @param generic type of the {@link AbstractListChromosome}s for crossover
* @since 3.1
*/
public class CycleCrossover implements CrossoverPolicy {
/** If the start index shall be chosen randomly. */
private final boolean randomStart;
/**
* Creates a new {@link CycleCrossover} policy.
*/
public CycleCrossover() {
this(false);
}
/**
* Creates a new {@link CycleCrossover} policy using the given {@code randomStart} behavior.
*
* @param randomStart whether the start index shall be chosen randomly or be set to 0
*/
public CycleCrossover(final boolean randomStart) {
this.randomStart = randomStart;
}
/**
* Returns whether the starting index is chosen randomly or set to zero.
*
* @return {@code true} if the starting index is chosen randomly, {@code false} otherwise
*/
public boolean isRandomStart() {
return randomStart;
}
/**
* {@inheritDoc}
*
* @throws MathIllegalArgumentException if the chromosomes are not an instance of {@link AbstractListChromosome}
* @throws DimensionMismatchException if the length of the two chromosomes is different
*/
@SuppressWarnings("unchecked")
public ChromosomePair crossover(final Chromosome first, final Chromosome second)
throws DimensionMismatchException, MathIllegalArgumentException {
if (!(first instanceof AbstractListChromosome && second instanceof AbstractListChromosome)) {
throw new MathIllegalArgumentException(LocalizedFormats.INVALID_FIXED_LENGTH_CHROMOSOME);
}
return mate((AbstractListChromosome) first, (AbstractListChromosome) second);
}
/**
* Helper for {@link #crossover(Chromosome, Chromosome)}. Performs the actual crossover.
*
* @param first the first chromosome
* @param second the second chromosome
* @return the pair of new chromosomes that resulted from the crossover
* @throws DimensionMismatchException if the length of the two chromosomes is different
*/
protected ChromosomePair mate(final AbstractListChromosome first, final AbstractListChromosome second)
throws DimensionMismatchException {
final int length = first.getLength();
if (length != second.getLength()) {
throw new DimensionMismatchException(second.getLength(), length);
}
// array representations of the parents
final List parent1Rep = first.getRepresentation();
final List parent2Rep = second.getRepresentation();
// and of the children: do a crossover copy to simplify the later processing
final List child1Rep = new ArrayList(second.getRepresentation());
final List child2Rep = new ArrayList(first.getRepresentation());
// the set of all visited indices so far
final Set visitedIndices = new HashSet(length);
// the indices of the current cycle
final List indices = new ArrayList(length);
// determine the starting index
int idx = randomStart ? GeneticAlgorithm.getRandomGenerator().nextInt(length) : 0;
int cycle = 1;
while (visitedIndices.size() < length) {
indices.add(idx);
T item = parent2Rep.get(idx);
idx = parent1Rep.indexOf(item);
while (idx != indices.get(0)) {
// add that index to the cycle indices
indices.add(idx);
// get the item in the second parent at that index
item = parent2Rep.get(idx);
// get the index of that item in the first parent
idx = parent1Rep.indexOf(item);
}
// for even cycles: swap the child elements on the indices found in this cycle
if (cycle++ % 2 != 0) {
for (int i : indices) {
T tmp = child1Rep.get(i);
child1Rep.set(i, child2Rep.get(i));
child2Rep.set(i, tmp);
}
}
visitedIndices.addAll(indices);
// find next starting index: last one + 1 until we find an unvisited index
idx = (indices.get(0) + 1) % length;
while (visitedIndices.contains(idx) && visitedIndices.size() < length) {
idx++;
if (idx >= length) {
idx = 0;
}
}
indices.clear();
}
return new ChromosomePair(first.newFixedLengthChromosome(child1Rep),
second.newFixedLengthChromosome(child2Rep));
}
}