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Parameter-Less Optimization with the Extended Compact Genetic Algorithm and Iterated Local Search
Cláudio F. Lima and Fernando G. Lobo
ADEEC-FCT, Universidade do Algarve, Campus de Gambelas, 8000 Faro, Portugalclima@ualg.pt
flobo@ualg.pt
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.
LNCS 3102, p. 1328 ff.
lncs@springer.de
© Springer-Verlag Berlin Heidelberg 2004