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

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

2004-02-19

arxiv.org/abs/cs/0402047v1

Computer Science

Neural and Evolutionary Computing

12 pages, submitted to gecco 2004

Scientific paper

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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