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New initialisation techniques for multi-objective local search: Application to the bi-objective permutation flowshop

Blot, A; López-Ibáñez, M; Kessaci, MÉ; Jourdan, L; (2018) New initialisation techniques for multi-objective local search: Application to the bi-objective permutation flowshop. In: Parallel Problem Solving from Nature – PPSN XV. (pp. pp. 323-334). Springer: Cham, Switzerland. Green open access

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Abstract

Given the availability of high-performing local search (LS) for single-objective (SO) optimisation problems, a successful approach to tackle their multi-objective (MO) counterparts is scalarisation-based local search (SBLS). SBLS strategies solve multiple scalarisations, aggregations of the multiple objectives into a single scalar value, with varying weights. They have been shown to work specially well as the initialisation phase of other types of MO local search, e.g., Pareto local search (PLS). A drawback of existing SBLS strategies is that the underlying SO-LS method is unaware of the MO nature of the problem and returns only a single solution, discarding any intermediate solutions that may be of interest. We propose here two new SBLS initialisation strategies (ChangeRestart and ChangeDirection) that overcome this drawback by augmenting the underlying SO-LS method with an archive of nondominated solutions used to dynamically update the scalarisations. The new strategies produce better results on the bi-objective permutation flowshop problem than other five SBLS strategies from the literature, not only on their own but also when used as the initialisation phase of PLS.

Type: Proceedings paper
Title: New initialisation techniques for multi-objective local search: Application to the bi-objective permutation flowshop
Event: International Conference on Parallel Problem Solving from Nature
ISBN-13: 9783319992525
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-319-99253-2_26
Publisher version: https://doi.org/10.1007/978-3-319-99253-2_26
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: Flowshop scheduling Local search Heuristics Multi-objective optimisation Combinatorial optimisation
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/10068020
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