Abstract
Local Genetic Algorithms are search procedures designed in order to provide an effective local search. Several Genetic Algorithm models have recently been presented with this aim. In this paper we present a new Binary-coded Local Genetic Algorithm based on a Steady-State Genetic Algorithm with a crowding replacement method. We have compared a Multi-Start Local Search based on the Binary-Coded Local Genetic Algorithm with other instances of this metaheuristic based on Local Search Procedures presented in the literature. The results show that, for a wide range of problems, our proposal consistently outperforms the other local search approaches. © Springer-Verlag Berlin Heidelberg 2006.
Cite
CITATION STYLE
García-Martínez, C., Lozano, M., & Molina, D. (2006). A local genetic algorithm for binary-coded problems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4193 LNCS, pp. 192–201). Springer Verlag. https://doi.org/10.1007/11844297_20
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