The royal road for genetic algorithms: Fitness landscapes and GA performance

Genetic algorithms (GAs) play a major role inmanyartiflcial-lifesystems,butthereisoften little detailed understanding of why the GA performs as it does, and little theoretical basis on which to characterize the types of fltness landscapes that lead to successful GA performance. In this paper we propose a strategy for addressing these issues. Our strategy consists of deflning a set of features offltnesslandscapesthatareparticularlyrelevant to the GA, and experimentally studying how various conflgurations of these features afiect the GA’s performance along a number of dimensions. In this paper we informally describe an initial set of proposed feature classes, describe in detail one such class (\Royal Road" functions), and present some initial experimental results concerning theroleofcrossoverand\buildingblocks"on landscapes constructed from features of this class.

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