Hybrid Metaheuristics for Multi-objective combinatorial optimization

Ehrgott, Matthias and Gandibleux, Xavier (2008) Hybrid Metaheuristics for Multi-objective combinatorial optimization. In: Hybrid Metaheuristics. Studies in Computational Intelligence . Springer, Berlin, pp. 221-259. ISBN 978-3-540-78294-0

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Abstract

Many real-world optimization problems can be modelled as combinatorial optimization problems. Often, these problems are characterized by their large size and the presence of multiple, conflicting objectives. Despite progress in solving multi-objective combinatorial optimization problems exactly, the large size often means that heuristics are required for their solution in acceptable time. Since the middle of the nineties the trend is towards heuristics that “pick and choose” elements from several of the established metaheuristic schemes. Such hybrid approximation techniques may even combine exact and heuristic approaches. In this chapter we give an overview over approximation methods in multi-objective combinatorial optimization. We briefly summarize “classical” metaheuristics and focus on recent approaches, where metaheuristics are hybridized and/or combined with exact methods.

Item Type: Contribution in Book/Report/Proceedings
Departments: Lancaster University Management School > Management Science
ID Code: 64435
Deposited By: ep_importer_pure
Deposited On: 10 May 2013 13:02
Refereed?: No
Published?: Published
Last Modified: 07 Jan 2020 03:22
URI: https://eprints.lancs.ac.uk/id/eprint/64435

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