A local genetic algorithm for binary-coded problems

Authors:
Carlos García-Martínez;Manuel Lozano;Daniel Molina
Affiliations:
Dept. of Computing and Numerical Analysis, Univ. of Córdoba, Spain;Dept. of Computer Science and Artificial Intelligence, Univ. of Granada, Spain;Dept. of Software Engineering, Univ. of Cádiz, Spain
Venue:
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Year:
2006

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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.