Abstract
Parameter control is still one of the main challenges in evolutionary computation. This paper is concerned with controlling selection operators on-the-fly. We perform an experimental comparison of such methods on three groups of test functions and conclude that varying selection pressure during a GA run often yields performance benefits, and therefore is a recommended option for designers and users of evolutionary algorithms.
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Vajda, P., Eiben, A.E., Hordijk, W. (2008). Parameter Control Methods for Selection Operators in Genetic Algorithms. In: Rudolph, G., Jansen, T., Beume, N., Lucas, S., Poloni, C. (eds) Parallel Problem Solving from Nature – PPSN X. PPSN 2008. Lecture Notes in Computer Science, vol 5199. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87700-4_62
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DOI: https://doi.org/10.1007/978-3-540-87700-4_62
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