The Impact of Variation Operators on the Performance of SMS-EMOA on the Bi-objective BBOB-2016 Test Suite

Anne Auger 1, 2 Dimo Brockhoff 2, 3 Nikolaus Hansen 1, 2 Dejan Tušar 2, 3 Tea Tušar 2, 3 Tobias Wagner 4
1 TAO - Machine Learning and Optimisation
CNRS - Centre National de la Recherche Scientifique : UMR8623, Inria Saclay - Ile de France, UP11 - Université Paris-Sud - Paris 11, LRI - Laboratoire de Recherche en Informatique
3 DOLPHIN - Parallel Cooperative Multi-criteria Optimization
Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Abstract : The S-metric-Selection Evolutionary Multi-objective Optimization Algorithm (SMS-EMOA) is one of the best-known indicator-based multi-objective optimization algorithms. It employs the S-metric or hypervolume indicator in its (steady-state) selection by deleting in each iteration the solution that has the smallest contribution to the hypervolume indicator. In the SMS-EMOA, the conceptual idea is this hypervolume-based selection. Hence the algorithm can, for example, be combined with several variation operators. Here, we benchmark two versions of SMS-EMOA which employ differential evolution (DE) and simulated binary crossover (SBX) with polynomial mutation (PM) respectively on the newly introduced bi-objective bbob-biobj test suite of the Comparing Continuous Optimizers (COCO) platform. The results un-surprisingly reveal that the choice of the variation operator is crucial for performance with a clear advantage of the DE variant on almost all functions.
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Proceedings of the 2016 Genetic and Evolutionary Computation Conference Companion (GECCO '16 Companion), Jul 2016, Denver, CO, United States. pp.1225 - 1232, 2016, 〈10.1145/2908961.2931705〉
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Anne Auger, Dimo Brockhoff, Nikolaus Hansen, Dejan Tušar, Tea Tušar, et al.. The Impact of Variation Operators on the Performance of SMS-EMOA on the Bi-objective BBOB-2016 Test Suite. Proceedings of the 2016 Genetic and Evolutionary Computation Conference Companion (GECCO '16 Companion), Jul 2016, Denver, CO, United States. pp.1225 - 1232, 2016, 〈10.1145/2908961.2931705〉. 〈hal-01435456〉

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