Pošík, P. - Baudiš, P.: Dimension Selection in Axis-Parallel Brent-STEP Method for Black-Box Optimization of Separable Continuous Functions. In Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation (GECCO Companion '15), Sara Silva (Ed.). ACM, New York, NY, USA, p. 1151-1158.
The recently proposed Brent-STEP algorithm was gener
alized for separable functions by performing axis-parallel
searches, interleaving the steps in individual dimensions in
a round-robin fashion. This article explores the possibility
to choose the dimension for the next step in a more “intel
ligent way”, i.e. to optimize first along dimensions which
are believed to bring the highest profit. We present here
the results for the epsilon-greedy strategy, and for a method
based on the internals of the Brent-STEP algorithm. Al
though the proposed methods work better than the round
robin strategy in some situations, due to the marginal im
provement they bring we suggest the round robin strategy
to be used, thanks to its simplicity.
en
dc.language.iso
en
en
dc.publisher
ACM
cze
dc.subject
Black-box optimization
en
dc.subject
Benchmarking
en
dc.subject
Line search
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dc.subject
Separable functions
en
dc.title
Dimension Selection in Axis-Parallel Brent-STEP Method for Black-Box Optimization of Separable Continuous Functions
