On the Virtues of Parameterized Uniform Crossover,

Abstract

Traditionally, genetic algorithms have relied upon 1 and 2-point crossover operators. Many recent empirical studies, however, have shown the benefits of higher numbers of crossover points. Some of the most intriguing recent work has focused on uniform crossover, which involves on the average L/2 crossover points for strings of length L. Theoretical results suggest that, from the view of hyperplane sampling disruption, uniform crossover has few redeeming features. However, a growing body of experimental evidence suggests otherwise. In this paper, we attempt to reconcile these opposing views of uniform crossover and present a framework for understanding its virtues. 1 Introduction One of the unique aspects of the work involving genetic algorithms (GAs) is the important role that recombination plays. In most GAs, recombination is implemented by means of a crossover operator which operates on pairs of individuals (parents) to produce new offspring by exchanging segments from the parents' ...