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Scalability of Selectorecombinative Genetic Algorithms for Problems with Tight Linkage

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Genetic and Evolutionary Computation — GECCO 2003 (GECCO 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2724))

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Abstract

Ensuring building-block (BB) mixing is critical to the success of genetic and evolutionary algorithms. This study develops facetwise models to predict the BB mixing time and the population sizing dictated by BB mixing for single-point crossover. The population-sizing model suggests that for moderate-to-large problems, BB mixing – instead of BB decision making and BB supply – bounds the population size required to obtain a solution of constant quality. Furthermore, the population sizing for single-point crossover scales as O (2k m 1.5), where k is the BB size, and m is the number of BBs.

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Sastry, K., Goldberg, D.E. (2003). Scalability of Selectorecombinative Genetic Algorithms for Problems with Tight Linkage. In: Cantú-Paz, E., et al. Genetic and Evolutionary Computation — GECCO 2003. GECCO 2003. Lecture Notes in Computer Science, vol 2724. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45110-2_8

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  • DOI: https://doi.org/10.1007/3-540-45110-2_8

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40603-7

  • Online ISBN: 978-3-540-45110-5

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