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2016

Biobjective Performance Assessment with the COCO Platform

Brockhoff, Dimo, Tušar, Tea, Tušar, Dejan et al.

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This document details the rationales behind assessing the performance of numerical black-box optimizers on multi-objective problems within the COCO platform and in particular on the biobjective test suite bbob-biobj.

The evaluation is based on a hypervolume of all non-dominated solutions in the archive of candidate solutions and measures the runtime until the hypervolume value succeeds prescribed target values.

Biobjective Performance Assessment with the COCO Platform · Around

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K. Deb, A. Pratap, S. Agarwal, and T. A. M. T. Meyarivan (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation , 6(2), pp. 182-197
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E. Zitzler, L. Thiele, M. Laumanns, C. M. Fonseca, and V. Grunert da Fonseca (2003). Performance Assessment of Multiobjective Optimizers: An Analysis and Review. IEEE Transactions on Evolutionary Computation , 7(2), pp. 117-132
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2003
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N. Beume, B. Naujoks, and M. Emmerich (2007). SMS-EMOA: Multiobjective selection based on dominated hypervolume. European Journal of Operational Research , 181(3), pp. 1653-1669
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Then

N. Hansen, A. Auger, D. Brockhoff, D. Tušar, T. Tušar (2016). COCO: Performance Assessment , ArXiv e-prints , arXiv:160x.xxxxx
2016
Closest in time.
N. Hansen, A. Auger, O. Mersmann, T. Tušar, D. Brockhoff (2016). COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting , ArXiv e-prints , arXiv:1603.08785
Original
2016
Closest in time.
N. Hansen, T. Tušar, A. Auger, D. Brockhoff, O. Mersmann (2016). COCO: The Experimental Procedure , ArXiv e-prints , arXiv:1603.08776
Original
2016
Closest in time.
T. Tušar, D. Brockhoff, N. Hansen, A. Auger (2016). COCO: The Bi-objective Black Box Optimization Benchmarking (bbob-biobj) Test Suite , ArXiv e-prints , arXiv:1604.00359
Original
2016
Closest in time.

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