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/*
* Chips-n-Salsa: A library of parallel self-adaptive local search algorithms.
* Copyright (C) 2002-2022 Vincent A. Cicirello
*
* This file is part of Chips-n-Salsa (https://chips-n-salsa.cicirello.org/).
*
* Chips-n-Salsa is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* Chips-n-Salsa is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see In a Gaussian mutation, a value v is mutated by adding a randomly generated m such that m is
* drawn from a Gaussian distribution with mean 0 and standard deviation sigma. It is commonly
* employed in Evolution Strategies when mutating real valued parameters.
*
*
This mutation operator also implements the {@link RealValued} interface to enable
* implementation of metaheuristics that mutate their own mutation parameters. That is, you can pass
* a GaussianMutation object to the {@link #mutate} method of a GaussianMutation object.
*
*
To construct a GaussianMutation, you must use one of the factory methods. See the various
* {@link #createGaussianMutation} methods.
*
*
Gaussian mutation was introduced in the following article:
* Hinterding, R. 1995. Gaussian mutation and self-adaption for numeric genetic algorithms. In IEEE
* CEC. IEEE Press. 384–389.
*
* @param The specific RealValued type.
* @author Vincent A. Cicirello, https://www.cicirello.org/
*/
public class GaussianMutation extends AbstractRealMutation
implements Copyable> {
/*
* Internal constructor. Constructs a Gaussian mutation operator.
* Otherwise, must use the factory methods.
*
* @param sigma The standard deviation of the Gaussian.
*
* @param transformer The functional transformation of the mutation.
*/
GaussianMutation(double sigma, DoubleBinaryOperator transformer) {
super(sigma, transformer);
}
/*
* Internal constructor. Constructs a Gaussian mutation operator.
* Otherwise, must use the factory methods.
*
* @param sigma The standard deviation of the Gaussian.
*
* @param transformer The functional transformation of the mutation.
*
* @param selector Chooses the indexes for a partial mutation.
*/
GaussianMutation(double sigma, DoubleBinaryOperator transformer, IntFunction selector) {
super(sigma, transformer, selector);
}
/*
* internal copy constructor
*/
GaussianMutation(GaussianMutation other) {
super(other);
}
/**
* Creates a Gaussian mutation operator with standard deviation equal to 1.
*
* @param The specific RealValued type.
* @return A Gaussian mutation operator.
*/
public static GaussianMutation createGaussianMutation() {
return createGaussianMutation(1.0);
}
/**
* Creates a Gaussian mutation operator.
*
* @param sigma The standard deviation of the Gaussian.
* @param The specific RealValued type.
* @return A Gaussian mutation operator.
*/
public static GaussianMutation createGaussianMutation(double sigma) {
return new GaussianMutation(sigma, (old, param) -> old + RandomVariates.nextGaussian(param));
}
/**
* Creates a Gaussian mutation operator, such that the mutate method constrains each mutated real
* value to lie in the interval [lowerBound, upperBound].
*
* @param sigma The standard deviation of the Gaussian.
* @param lowerBound A lower bound on the result of a mutation.
* @param upperBound An upper bound on the result of a mutation.
* @param The specific RealValued type.
* @return A Gaussian mutation operator.
*/
public static GaussianMutation createGaussianMutation(
double sigma, double lowerBound, double upperBound) {
if (upperBound < lowerBound)
throw new IllegalArgumentException("upperBound must be at least lowerBound");
return new GaussianMutation(
sigma,
(old, param) -> {
double mutated = old + RandomVariates.nextGaussian(param);
if (mutated <= lowerBound) return lowerBound;
if (mutated >= upperBound) return upperBound;
return mutated;
});
}
/**
* Create a Gaussian mutation operator.
*
* @param sigma The standard deviation of the Gaussian mutation.
* @param k The number of input variables that the {@link #mutate} method changes when called. The
* k input variables are chosen uniformly at random from among all subsets of size k. If there
* are less than k input variables, then all are mutated.
* @param The specific RealValued type.
* @return A Gaussian mutation operator
* @throws IllegalArgumentException if k < 1
*/
public static GaussianMutation createGaussianMutation(
double sigma, int k) {
if (k < 1) throw new IllegalArgumentException("k must be at least 1");
return new GaussianMutation(
sigma,
(old, param) -> old + RandomVariates.nextGaussian(param),
n -> RandomSampler.sample(n, k < n ? k : n, (int[]) null));
}
/**
* Create a Gaussian mutation operator.
*
* @param sigma The standard deviation of the Gaussian mutation.
* @param p The probability that the {@link #mutate} method changes an input variable. If there
* are n input variables, then n*p input variables will be mutated on average during a single
* call to the {@link #mutate} method.
* @param The specific RealValued type.
* @return A Gaussian mutation operator
* @throws IllegalArgumentException if p ≤ 0
*/
public static GaussianMutation createGaussianMutation(
double sigma, double p) {
if (p <= 0) throw new IllegalArgumentException("p must be positive");
if (p >= 1) {
return createGaussianMutation(sigma);
}
return new GaussianMutation(
sigma,
(old, param) -> old + RandomVariates.nextGaussian(param),
n -> RandomSampler.sample(n, p));
}
@Override
public GaussianMutation split() {
return new GaussianMutation(this);
}
/**
* Creates an identical copy of this object.
*
* @return an identical copy of this object
*/
@Override
public GaussianMutation copy() {
return new GaussianMutation(this);
}
}