Blot, A;
Kessaci, M-É;
Jourdan, L;
Hoos, HH;
(2019)
Automatic Configuration of Multi-Objective Local Search Algorithms for Permutation Problems.
Evolutionary Computation
, 27
(1)
pp. 147-171.
10.1162/evco_a_00240.
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Abstract
Automatic algorithm configuration (AAC) is becoming a key ingredient in the design of high-performance solvers for challenging optimisation problems. However, most existing work on AAC deals with configuration procedures that optimise a single performance metric of a given, single-objective algorithm. Of course, these configurators can also be used to optimise the performance of multi-objective algorithms, as measured by a single performance indicator. In this work, we demonstrate that better results can be obtained by using a native, multi-objective algorithm configuration procedure. Specifically, we compare three AAC approaches: one considering only the hypervolume indicator, a second optimising the weighted sum of hypervolume and spread, and a third that simultaneously optimises these complementary indicators, using a genuinely multi-objective approach. We assess these approaches by applying them to a highly-parametric local search framework for two widely studied multi-objective optimisation problems, the bi-objective permutation flowshop and travelling salesman problems. Our results show that multi-objective algorithms are indeed best configured using a multi-objective configurator.
| Type: | Article |
|---|---|
| Title: | Automatic Configuration of Multi-Objective Local Search Algorithms for Permutation Problems |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1162/evco_a_00240 |
| Publisher version: | https://doi.org/10.1162/evco_a_00240 |
| 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, local search, multi-objective optimisation, permutation flowshop scheduling problem, travelling salesman problem. |
| 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/10068019 |
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