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Automatically configuring multi-objective local search using multi-objective optimisation

Blot, A; Pernet, A; Jourdan, L; Kessaci-Marmion, M; Hoos, H; (2017) Automatically configuring multi-objective local search using multi-objective optimisation. In: Evolutionary Multi-Criterion Optimization. (pp. pp. 61-76). Springer: Cham, Switzerland. Green open access

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Abstract

Automatic algorithm configuration (AAC) is becoming an increasingly crucial component in the design of high-performance solvers for many challenging combinatorial optimisation problems. This raises the question how to most effectively leverage AAC in the context of building or optimising multi-objective optimisation algorithms, and specifically, multi-objective local search procedures. Because the performance of multi-objective optimisation algorithms cannot be fully characterised by a single performance indicator, we believe that AAC for multi-objective local search should make use of multi-objective configuration procedures. We test this belief by using MO-ParamILS to automatically configure a highly parametric iterated local search framework for the classical and widely studied bi-objective permutation flowshop problem. To the best of our knowledge, this is the first time a multi-objective optimisation algorithm is automatically configured in a multi-objective fashion, and our results demonstrate that this approach can produce very good results as well as interesting insights into the efficacy of various strategies and components of a flexible multi-objective local search framework.

Type: Proceedings paper
Title: Automatically configuring multi-objective local search using multi-objective optimisation
Event: International Conference on Evolutionary Multi-Criterion Optimization
ISBN-13: 9783319541563
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-319-54157-0_5
Publisher version: https://doi.org/10.1007/978-3-319-54157-0_5
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: Algorithm configuration, Multi-objective optimisation, Local search, Permutation flowshop scheduling
UCL classification: 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: http://discovery.ucl.ac.uk/id/eprint/10068022
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