Open AccessBenchmarking RM-MEDA on the Bi-objective BBOB-2016 Test Suite
Author(s) -
Anne Auger,
Dimo Brockhoff,
Nikolaus Hansen,
Dejan Tušar,
Tea Tušar,
Tobias Wagner
Publication year - 2016
Publication title -
hal (le centre pour la communication scientifique directe)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1145/2908961.2931707
Subject(s) - benchmarking , benchmark (surveying) , test suite , suite , dimension (graph theory) , mathematics , function (biology) , mathematical optimization , computer science , algorithm , combinatorics , test case , marketing , history , geodesy , archaeology , geography , evolutionary biology , biology , business
International audienceIn this paper, we benchmark the Regularity Model-Based Multiobjective Estimation of Distribution Algorithm (RM-MEDA) of Zhang et al. on the bi-objective bbob-biobj test suite of the Comparing Continuous Optimizers (COCO) platform. It turns out that, starting from about 200 times dimension many function evaluations, RM-MEDA shows a linear increase in the solved hypervolume-based target values with time until a stagnation of the performance occurs rather quickly on all problems. The final percentage of solved hy-pervolume targets seems to decrease with the problem dimension
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