Blot, A;
Kessaci, MÉ;
Jourdan, L;
De Causmaecker, P;
(2018)
Adaptive multi-objective local search algorithms for the permutation flowshop scheduling problem.
In:
International Conference on Learning and Intelligent Optimization.
(pp. pp. 241-256).
Springer: Cham, Switzerland.
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Abstract
Automatic algorithm configuration (AAC) is an increasingly critical factor in the design of efficient metaheuristics. AAC was previously successfully applied to multi-objective local search (MOLS) algorithms using offline tools. However, offline approaches are usually very expensive, draw general recommendations regarding algorithm design for a given set of instances, and does generally not allow per-instance adaptation. Online techniques for automatic algorithm control are usually applied to single-objective evolutionary algorithms. In this work we investigate the impact of including control mechanisms to MOLS algorithms on a classical bi-objective permutation flowshop scheduling problem (PFSP), and demonstrate how even simple control mechanisms can complement traditional offline configuration techniques.
Type: | Proceedings paper |
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Title: | Adaptive multi-objective local search algorithms for the permutation flowshop scheduling problem |
Event: | International Conference on Learning and Intelligent Optimization LION 12 2018 |
Location: | Kalamata, Greece |
Dates: | 10-15 June 2018 |
ISBN-13: | 9783030053475 |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1007/978-3-030-05348-2_22 |
Publisher version: | https://doi.org/10.1007/978-3-030-05348-2_22 |
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. |
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/10068495 |
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