Benchmarking MO-CMA-ES and COMO-CMA-ES on the bi-objective bbob-biobj testbed | Zendy

Paul Dufossé | Zendy; Cheikh Touré | Zendy

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Benchmarking MO-CMA-ES and COMO-CMA-ES on the bi-objective bbob-biobj testbed

Author(s) -

Paul Dufossé,

Cheikh Touré

Publication year - 2019

Publication title -

proceedings of the genetic and evolutionary computation conference companion

Language(s) - English

Resource type - Conference proceedings

ISBN - 978-1-4503-6748-6

DOI - 10.1145/3319619.3326892

Subject(s) - testbed , benchmark (surveying) , benchmarking , cma es , suite , computer science , test suite , mathematical optimization , mathematics , algorithm , evolution strategy , evolutionary algorithm , artificial intelligence , machine learning , test case , computer network , regression analysis , geodesy , archaeology , marketing , business , history , geography

In this paper, we propose a comparative benchmark of MO-CMA-ES, COMO-CMA-ES (recently introduced in [12]) and NSGA-II, using the COCO framework for performance assessment and the Bi-objective test suite bbob-biobj. For a fixed number of points p, COMO-CMA-ES approximates an optimal p-distribution of the Hypervolume Indicator. While not designed to perform on archive-based assessment, i.e. with respect to all points evaluated so far by the algorithm, COMO-CMA-ES behaves well on the COCO platform. The experiments are done in a true Black-Blox spirit by using a minimal setting relative to the information shared by the 55 problems of the bbob-biobj Testbed.

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