Abstract

HERNANDEZ-OCANA, Betania et al. Bacterial foraging optimization algorithm with mutation to solve constrained problems. Acta univ [online]. 2019, vol.29, e2335.  Epub Sep 11, 2020. ISSN 2007-9621.  https://doi.org/10.15174/au.2019.2335.

A simple version of a Swarm Intelligence algorithm called bacterial foraging optimization algorithm with mutation and dynamic stepsize (BFOAM-DS) is proposed. The bacterial foraging algorithm has the ability to explore and exploit the search space through its chemotactic operator. However, premature convergence is a disadvantage. This proposal uses a mutation operator in a swim, similar to evolutionary algorithms, combined with a dynamic stepsize operator to improve its performance and allows a better balance between the exploration and exploitation of the search space. BFOAM-DS was tested in three well-known engineering design optimization problems. Results were analyzed with basic statistics and common measures for nature-inspired constrained optimization problems to evaluate the behavior of the swim with a mutation operator and the dynamic stepsize operator. Results were compared against a previous version of the proposed algorithm to conclude that BFOAM-DS is competitive and better than a previous version of the algorithm.

Keywords : Metaheuristic; mutation operator; dynamic stepsize; engineering problem; performance measures.

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