Distribution tree-building real-valued evolutionary algorithm

Abstract

This article describes a new model of probability density function and its use in estimation of distribution algorithms. The new model, the distribution tree, has interesting properties and can form a solid basis for further improvements which will make it even more competitive. Several comparative experiments on continuous real-valued optimization problems were carried out and the results are promising. It outperformed the genetic algorithm using the traditional crossover operator several times, in the majority of the remaining experiments it was comparable to the genetic algorithm performance. © Springer-Verlag 2004.