Evolutionary algorithms and cross entropy

Authors:
Colin Fyfe;Domingo Ortiz-Boyer;Nicolas Garcia-Pedrajas
Affiliations:
The University of the West of Scotland, Paisley, UK;Cordoba University, Cordoba, Spain;Cordoba University, Cordoba, Spain
Venue:
International Journal of Knowledge-based and Intelligent Engineering Systems
Year:
2012

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Abstract

Cross entropy is a method designed to estimate some statistic pertaining to events of very low probability. We discuss cross entropy with respect to optimisation problems and then illustrate the cross entropy method on a specific function Rosenbrock's function which we have found to be difficult to optimise using evolutionary algorithms. We examine the convergence of the cross entropy method to identify why evolutionary algorithms find this difficult. We then use a concept from evolutionary algorithms that of separate sub-populations to enhance the cross entropy method.