Pageau, C;
Blot, A;
Hoos, HH;
Kessaci, ME;
Jourdan, L;
(2019)
Configuration of a dynamic MOLS algorithm for Bi-objective flowshop scheduling.
In: Deb, K and Goodman, E and Coello Coello, CA and Klamroth, K and Miettinen, K and Mostaghim, S and Reed, P, (eds.)
Evolutionary Multi-Criterion Optimization: 10th International Conference, EMO 2019, East Lansing, MI, USA, March 10-13, 2019, Proceedings.
(pp. pp. 565-577).
Springer: Cham, Switzerland.
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Abstract
In this work, we propose a dynamic multi-objective local search (MOLS) algorithm whose parameters are modified while it is running and a protocol for automatically configuring this algorithm. Our approach applies automated configuration to a static pipeline that sequentially runs multiple configurations of the MOLS algorithm. In a series of experiments for well-known benchmark instances of the bi-objective permutation flowshop scheduling problem, we show that our dynamic approach produces substantially better results than static MOLS, and that longer pipeline (with a higher number of parameters) outperform shorter ones.
| Type: | Proceedings paper |
|---|---|
| Title: | Configuration of a dynamic MOLS algorithm for Bi-objective flowshop scheduling |
| Event: | 10th International Conference, 10th - 13th March 2019, East Lansing, MI, USA |
| ISBN-13: | 9783030125974 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/978-3-030-12598-1_45 |
| Publisher version: | https://doi.org/10.1007/978-3-030-12598-1_45 |
| 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 combinatorial optimisation, Local search |
| 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/10073107 |
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