ExponentialRankSelector.java
/*
* 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;
import static java.lang.Math.pow;
import static java.lang.String.format;
import static org.jenetics.internal.util.object.eq;
import javolution.lang.Immutable;
import org.jenetics.internal.util.HashBuilder;
/**
* <p>
* An alternative to the "weak" {@code LinearRankSelector} is to assign
* survival probabilities to the sorted individuals using an exponential
* function.
* </p>
* <p><img
* src="doc-files/exponential-rank-selector.gif"
* alt="P(i)=\left(c-1\right)\frac{c^{i-1}}{c^{N}-1}"
* >,
* </p>
* where <i>c</i> must within the range {@code [0..1)}.
*
* <p>
* A small value of <i>c</i> increases the probability of the best phenotypes to
* be selected. If <i>c</i> is set to zero, the selection probability of the best
* phenotype is set to one. The selection probability of all other phenotypes is
* zero. A value near one equalizes the selection probabilities.
* </p>
* <p>
* This selector sorts the population in descending order while calculating the
* selection probabilities.
* </p>
*
* @author <a href="mailto:franz.wilhelmstoetter@gmx.at">Franz Wilhelmstötter</a>
* @since 1.0
* @version 1.0 — <em>$Date: 2014-03-01 $</em>
*/
public final class ExponentialRankSelector<
G extends Gene<?, G>,
C extends Comparable<? super C>
>
extends ProbabilitySelector<G, C>
implements Immutable
{
private final double _c;
/**
* Create a new exponential rank selector.
*
* @param c the <i>c</i> value.
* @throws IllegalArgumentException if {@code c} is not within the range
* {@code [0..1)}.
*/
public ExponentialRankSelector(final double c) {
if (c < 0.0 || c >= 1.0) {
throw new IllegalArgumentException(format(
"Value %s is out of range [0..1): ", c
));
}
_c = c;
}
/**
* This method sorts the population in descending order while calculating the
* selection probabilities. (The method {@link Population#sort()} is called
* by this method.)
*/
@Override
protected double[] probabilities(
final Population<G, C> population,
final int count
) {
assert(population != null) : "Population can not be null. ";
assert(count > 0) : "Population to select must be greater than zero. ";
//Sorted population required.
population.sort();
final double N = population.size();
final double[] probabilities = new double[population.size()];
final double b = pow(_c, N) - 1;
for (int i = probabilities.length; --i >= 0;) {
probabilities[i] = ((_c - 1)*pow(_c, i))/b;
}
assert (sum2one(probabilities)) : "Probabilities doesn't sum to one.";
return probabilities;
}
@Override
public int hashCode() {
return HashBuilder.of(getClass()).and(_c).value();
}
@Override
public boolean equals(final Object obj) {
if (obj == this) {
return true;
}
if (obj == null || obj.getClass() != getClass()) {
return false;
}
final ExponentialRankSelector<?, ?> selector = (ExponentialRankSelector<?, ?>)obj;
return eq(_c, selector._c);
}
@Override
public String toString() {
return format("%s[c=%f]", getClass().getSimpleName(), _c);
}
}