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.
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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 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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