2003 | OriginalPaper | Buchkapitel
Population Implosion in Genetic Programming
verfasst von : Sean Luke, Gabriel Catalin Balan, Liviu Panait
Erschienen in: Genetic and Evolutionary Computation — GECCO 2003
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
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With the exception of a small body of adaptive-parameter literature, evolutionary computation has traditionally favored keeping the population size constant through the course of the run. Unfortunately, genetic programming has an aging problem: for various reasons, late in the run the technique become less effective at optimization. Given a fixed number of evaluations, allocating many of them late in the run may thus not be a good strategy. In this paper we experiment with gradually decreasing the population size throughout a genetic programming run, in order to reallocate more evaluations to early generations. Our results show that over four problem domains and three different numbers of evaluations, decreasing the population size is always as good as, and frequently better than, various fixed-sized population strategies.