Selection Intensity in Asynchronous Cellular Evolutionary Algorithms

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This paper presents a theoretical study of the selection pressure in asynchronous cellular evolutionary algorithms (cEAs). This work is motivated by the search for a general model for asynchronous update of the individuals in a cellular EA, and by the necessity of better accuracy beyond what existing models of selection intensity can provide. Therefore, we investigate the differences between the expected and actual values of the selection pressure induced by several asynchronous update policies, and formally characterize the update dynamics of each variant of the algorithm. New models for these two issues are proposed, and are shown to be more accurate (lower fit error) than previous ones.