Performance of a Genetic Algorithm with Variable Local Search Range Relative to Frequency of the Environmental Changes

Abstract

Although the genetic algorithm is a robust search technique, it is often unable to redirect its search to a different part of the search space, should the search landscape change. The variable local search operator was designed to enable the genetic algorithm to track optima of time-varying systems. It constitutes an adaptive tracking mechanism as it is triggered only when the running average of the best performing members of the population deteriorates. In this paper we compare the performance of the genetic algorithm which implements the variable local search operator with two alternative tracking mechanisms for periodically occurring environmental changes. The main advantage of the new tracking technique is that the VLS operator is able to provide sound results even for high frequencies of environmental change provided the degree of the change is relatively small as the search is initially confined to a restricted part of the fitness landscape. This is an important feature of the ne..