Conference Papers Year : 2019

The Impact of Sample Volume in Random Search on the bbob Test Suite

Abstract

Uniform Random Search is considered the simplest of all randomized search strategies and thus a natural baseline in benchmarking. Yet, in continuous domain it has its search domain width as a parameter that potentially has a strong effect on its performance. In this paper, we investigate this effect on the well-known 24 functions from the bbob test suite by varying the sample domain of the algorithm ([−α, α]^n for α ∈ {0.5, 1, 2, 3, 4, 5, 6, 10, 20} and n the search space dimension). Though the optima of the bbob testbed are randomly chosen in [−4, 4]^n (with the exception of the linear function f5), the best strategy depends on the search space dimension and the chosen budget. Small budgets and larger dimensions favor smaller domain widths.
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Dates and versions

hal-02171213 , version 1 (02-07-2019)

Identifiers

Cite

Dimo Brockhoff, Nikolaus Hansen. The Impact of Sample Volume in Random Search on the bbob Test Suite. GECCO '19 Companion: The Genetic and Evolutionary Computation Conference, Jul 2019, Prague, Czech Republic. ⟨10.1145/3319619.3326894⟩. ⟨hal-02171213⟩
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