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Parameter-Less Optimization with the Extended Compact Genetic Algorithm and Iterated Local Search

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Genetic and Evolutionary Computation – GECCO 2004 (GECCO 2004)

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Abstract

This paper presents a parameter-less optimization framework that uses the extended compact genetic algorithm (ECGA) and iterated local search (ILS), but is not restricted to these algorithms. The presented optimization algorithm (ILS+ECGA) comes as an extension of the parameter-less genetic algorithm (GA), where the parameters of a selecto-recombinative GA are eliminated. The approach that we propose is tested on several well known problems. In the absence of domain knowledge, it is shown that ILS+ECGA is a robust and easy-to-use optimization method.

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Lima, C.F., Lobo, F.G. (2004). Parameter-Less Optimization with the Extended Compact Genetic Algorithm and Iterated Local Search. In: Deb, K. (eds) Genetic and Evolutionary Computation – GECCO 2004. GECCO 2004. Lecture Notes in Computer Science, vol 3102. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24854-5_127

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  • DOI: https://doi.org/10.1007/978-3-540-24854-5_127

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22344-3

  • Online ISBN: 978-3-540-24854-5

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