Unbounded population MO-CMA-ES for the bi-objective BBOB test suite

Oswin Krause; Tobias Glasmachers; Nikolaus Hansen; Christian Igel

doi:10.1145/2908961.2931699

Unbounded population MO-CMA-ES for the bi-objective BBOB test suite

Oswin Krause, Tobias Glasmachers, Nikolaus Hansen, Christian Igel

Datalogisk Institut

13 Citationer (Scopus)

Abstract

The unbounded population multi-objective covariance matrix adaptation evolution strategy∼(UP-MO-CMA-ES) aims at maximizing the total hypervolume covered by all evaluated points. It adds all non-dominated solutions found to its population and employs Gaussian mutations with adaptive covariance matrices to also solve ill-conditioned problems. A novel recombination operator adapts the covariance matrices to point along the Pareto front. The UP-MO-CMA-ES is combined with a parallel exploration strategy and empirically evaluated on the bi-objective BBOB-biobj benchmark problems. Results show that the algorithm can reliably solve ill-conditioned problems as well as weakly-structured problems. However, it is less suited for the rugged multi-modal objective functions in the benchmark.

Originalsprog	Engelsk
Titel	Proceedings of the 2016 Genetic and Evolutionary Computation Conference Companion
Antal sider	8
Forlag	Association for Computing Machinery
Publikationsdato	20 jul. 2016
Sider	1177-1184
ISBN (Trykt)	978-1-4503-4323-7
DOI	https://doi.org/10.1145/2908961.2931699
Status	Udgivet - 20 jul. 2016
Begivenhed	Genetic and Evolutionary Computation Conference - Denver, USA Varighed: 20 jul. 2016 → 24 jul. 2016

Konference

Konference	Genetic and Evolutionary Computation Conference
Land/Område	USA
By	Denver
Periode	20/07/2016 → 24/07/2016

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10.1145/2908961.2931699

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Unbounded population MO-CMA-ES for the bi-objective BBOB test suite. / Krause, Oswin; Glasmachers, Tobias; Hansen, Nikolaus et al.

Proceedings of the 2016 Genetic and Evolutionary Computation Conference Companion. Association for Computing Machinery, 2016. s. 1177-1184.

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › peer review

Krause, O, Glasmachers, T, Hansen, N & Igel, C 2016, Unbounded population MO-CMA-ES for the bi-objective BBOB test suite. i Proceedings of the 2016 Genetic and Evolutionary Computation Conference Companion. Association for Computing Machinery, s. 1177-1184, Genetic and Evolutionary Computation Conference, Denver, USA, 20/07/2016. https://doi.org/10.1145/2908961.2931699

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Unbounded population MO-CMA-ES for the bi-objective BBOB test suite

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