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Benchmarking Algorithms from the platypus Framework on the Biobjective bbob-biobj Testbed

Abstract : One of the main goals of the COCO platform is to produce, collect , and make available benchmarking performance data sets of optimization algorithms and, more concretely, algorithm implementations. For the recently proposed biobjective bbob-biobj test suite, less than 20 algorithms have been benchmarked so far but many more are available to the public. We therefore aim in this paper to benchmark several available multiobjective optimization algorithms on the bbob-biobj test suite and discuss their performance. We focus here on algorithms implemented in the platypus framework (in Python) whose main advantage is its ease of use without the need to set up many algorithm parameters.
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https://hal.inria.fr/hal-02171136
Contributor : Dimo Brockhoff <>
Submitted on : Tuesday, July 2, 2019 - 4:29:04 PM
Last modification on : Thursday, May 20, 2021 - 9:06:02 AM

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Dimo Brockhoff, Tea Tušar. Benchmarking Algorithms from the platypus Framework on the Biobjective bbob-biobj Testbed. GECCO 2019 - The Genetic and Evolutionary Computation Conference, Jul 2019, Prague, Czech Republic. ⟨10.1145/3319619.3326896⟩. ⟨hal-02171136⟩

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