Abstract

In this study we apply the African buffalo optimization (ABO) to solve benchmark global optimization problems. Such problems which are artificial representation of different search landscapes ranging from unimodal to multimodal, separable to non-separable, constrained to unconstrained search landscapes have become a veritable instrument to test the search capacities of optimization algorithms. After a number of experimental procedures involving 28 benchmark problems, results from ABO prove to be rather competitive leading to the conclusion that it is a worthy addition to the body of swarm intelligence techniques.

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