@inproceedings{4110ed4155aa4713b6e1e13e43b58224,
title = "Benchmarking RM-MEDA on the bi-objective BBOB-2016 test suite",
abstract = "In this paper, we benchmark the Regularity Model-Based Multiobjective Estimation of Distribution Algorithm family RM-MEDA of Zhang et al. on the bi-objective family bbob-biobj test suite of the Comparing Continuous Optimizers (COCO) platform. It turns out that, starting from about 200 times dimension many function evaluations, family 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 hypervolume targets seems to decrease with the problem dimension.",
keywords = "Benchmarking, Bi-objective optimization, Black-box optimization",
author = "Anne Auger and Dimo Brockhoff and Nikolaus Hansen and Dejan Tu{\v s}ar and Tea Tuar and Tobias Wagner",
note = "Publisher Copyright: {\textcopyright} 2016 ACM.; 2016 Genetic and Evolutionary Computation Conference, GECCO 2016 Companion ; Conference date: 20-07-2016 Through 24-07-2016",
year = "2016",
month = jul,
day = "20",
doi = "10.1145/2908961.2931707",
language = "English",
series = "GECCO 2016 Companion - Proceedings of the 2016 Genetic and Evolutionary Computation Conference",
publisher = "Association for Computing Machinery, Inc",
pages = "1241--1247",
editor = "Tobias Friedrich",
booktitle = "GECCO 2016 Companion - Proceedings of the 2016 Genetic and Evolutionary Computation Conference",
}