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.
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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 |
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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 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/10068022 |
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