A Java Implementation of Parameter-less Evolutionary Algorithms

TL;DR

This paper introduces P-EAJava, a Java platform that consolidates various parameter-less evolutionary algorithms, simplifying their application and extension for solving optimization problems without manual parameter tuning.

Contribution

It provides a unified Java implementation of multiple parameter-less evolutionary algorithms, facilitating easier use and development of such algorithms.

Findings

Includes parameter-less versions of several algorithms like SGA and HBEA.

Provides detailed usage and implementation instructions.

Available as free open-source software.

Abstract

The Parameter-less Genetic Algorithm was first presented by Harik and Lobo in 1999 as an alternative to the usual trial-and-error method of finding, for each given problem, an acceptable set-up of the parameter values of the genetic algorithm. Since then, the same strategy has been successfully applied to create parameter-less versions of other population-based search algorithms such as the Extended Compact Genetic Algorithm and the Hierarchical Bayesian Optimization Algorithm. This report describes a Java implementation, Parameter-less Evolutionary Algorithm (P-EAJava), that integrates several parameter-less evolutionary algorithms into a single platform. Along with a brief description of P-EAJava, we also provide detailed instructions on how to use it, how to implement new problems, and how to generate new parameter-less versions of evolutionary algorithms. At present time, P-EAJava already includes parameter-less versions of the Simple Genetic Algorithm, the Extended Compact Genetic Algorithm, the Univariate Marginal Distribution Algorithm, and the Hierarchical Bayesian Optimization Algorithm. The source and binary files of the Java implementation of P-EAJava are available for free download at https://github.com/JoseCPereira/2015ParameterlessEvolutionaryAlgorithmsJava.