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Survey and unification of local search techniques in metaheuristics for multi-objective combinatorial optimisation

Blot, A; Kessaci, MÉ; Jourdan, L; (2018) Survey and unification of local search techniques in metaheuristics for multi-objective combinatorial optimisation. Journal of Heuristics , 24 (6) pp. 853-877. 10.1007/s10732-018-9381-1. Green open access

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Abstract

© 2018, Springer Science+Business Media, LLC, part of Springer Nature. Metaheuristics are algorithms that have proven their efficiency on multi-objective combinatorial optimisation problems. They often use local search techniques, either at their core or as intensification mechanisms, to obtain a well-converged and diversified final result. This paper surveys the use of local search techniques in multi-objective metaheuristics and proposes a general structure to describe and unify their underlying components. This structure can instantiate most of the multi-objective local search techniques and algorithms in literature.

Type: Article
Title: Survey and unification of local search techniques in metaheuristics for multi-objective combinatorial optimisation
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/s10732-018-9381-1
Publisher version: https://doi.org/10.1007/s10732-018-9381-1
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Multi-objective optimisation, Combinatorial optimisation, Metaheuristics, Unification, Local search algorithms
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10068018
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