Expensive optimization scenario: IPOP-CMA-ES with a population bound mechanism for noiseless function testbed

Authors:
Tianjun Liao;Thomas Stützle
Affiliations:
IRIDIA, CoDE, Université Libre de Bruxelles, Brussels, Belgium;IRIDIA, CoDE, Université Libre de Bruxelles, Brussels, Belgium
Venue:
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Year:
2013

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Abstract

In this paper, we test the results from the default and tuned IPOP-CMA-ES with population bound mechanism (labeled as def and texp, respectively) [8, 9] on the expensive optimization scenario of the BBOB benchmark. In texp [9], seven parameters that directly control the internal parameters were tuned by applying an automatic algorithm configuration tool on the solution quality after 100 × D function evaluations. We compare the results of texp to those of the default variant (def) [8,9] in the expensive optimization scenario. We find that texp often converges faster than def.