Inproceedings,

An Empirical Study on GAs \"Without Parameters\"

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PPSN VI: Proceedings of the 6th International Conference on Parallel Problem Solving from Nature, page 315--324. London, UK, Springer-Verlag, (2000)

Abstract

In this paper we implement GAs that have one or more parameters that are adjusted during the run. In particular we use an existing self-adaptive mutation rate mechanism, propose a new mechanism for self-adaptive crossover rates, and redesign an existing variable population size model. We compare the simple GA with GAs featuring only one of the parameter adjusting mechanisms and with a GA that applies all three mechanisms - and is therefore almost "parameterless". The experimental results on a carefully designed test suite indicate the superiority of the parameterless GA and give a hint on the power of adapting the population size.

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