Abstract
Nature-inspired metaheuristics are effective strategies for solving optimization problems. However, when trying to solve an instance of this kind of problems it is hard to know which algorithm should be used (algorithm-instance problem). Hybrid systems provide flexible tools that can help to cope with this problem. Therefore a hybrid system based on the intelligent combination of different natureinspired strategies will give more robustness and will allow to find higher quality solutions for different instance types.
In this paper we show the construction of a nature-inspired hybrid system, and analyse a study case.
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Cadenas, J.M., Garrido, M.C., Muñoz, E. (2008). A Hybrid System of Nature Inspired Metaheuristics. In: Krasnogor, N., Nicosia, G., Pavone, M., Pelta, D. (eds) Nature Inspired Cooperative Strategies for Optimization (NICSO 2007). Studies in Computational Intelligence, vol 129. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78987-1_9
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DOI: https://doi.org/10.1007/978-3-540-78987-1_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-78986-4
Online ISBN: 978-3-540-78987-1
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