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The Impact of Variation Operators on the Performance of SMS-EMOA on the Bi-objective BBOB-2016 Test Suite
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.
Cited literature [11 references]
https://hal.inria.fr/hal-01435456
Contributor : Dimo Brockhoff <>
Submitted on : Saturday, January 14, 2017 - 12:53:45 AM
Last modification on : Friday, April 30, 2021 - 10:00:34 AM
Long-term archiving on: : Saturday, April 15, 2017 - 12:23:20 PM
Contributor : Dimo Brockhoff <>
Submitted on : Saturday, January 14, 2017 - 12:53:45 AM
Last modification on : Friday, April 30, 2021 - 10:00:34 AM
Long-term archiving on: : Saturday, April 15, 2017 - 12:23:20 PM
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