Abstract
A hybrid genetic algorithm based in local search is described. Local optimisation is not explicitly performed but it is embedded in the exploration of a search metaspace. This algorithm is applied to a NP-hard problem. When it is compared with other GA-based approaches and an exact technique (a branch and bound algorithm), this algorithm exhibits a better overall performance in both cases. Then, a coarse-grain parallel version is tested, yielding notably improved results.
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© 1998 Springer-Verlag Wien
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Cotta, C., Troya, J.M. (1998). A Hybrid Genetic Algorithm for the 0–1 Multiple Knapsack Problem. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6492-1_55
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DOI: https://doi.org/10.1007/978-3-7091-6492-1_55
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-83087-1
Online ISBN: 978-3-7091-6492-1
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