Abstract
The Genetic Neighborhood Search (GNS) is a hybrid method for combinatorial optimization problems. A main feature of the approach is the iterative use of local search on extended neighborhoods, where the better solution will be the center of a new extended neighborhood. We propose using a genetic algorithm to explore the extended neighborhoods. Computational experiences show that this approach is robust with respect to the starting point and that high quality solutions are obtained in reasonable time. © Springer-Verlag 2002.
Cite
CITATION STYLE
Domínguez, J. J., Lozano, S., & Calle, M. (2002). Genetic neighborhood search. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2331 LNCS, pp. 544–553). Springer Verlag. https://doi.org/10.1007/3-540-47789-6_57
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