Abstract

Magnetotactic bacteria optimization algorithm (MBOA) is an optimization algorithm based on the characteristics of magnetotactic bacteria, which is a kind of polyphyletic group of prokaryotes with the characteristics of magnetotaxis that make them orient and swim along geomagnetic field lines. MBOA mimics the development process of magnetosomes (MTSs) in magnetotactic bacteria to solve problems. In this paper, four improved MBOAs are researched. Four pairwise MTSs regulation schemes based on the best individual and randomly chosen one are proposed in order to study which scheme is more suitable for solving optimization problems. They are tested on fourteen standard function problems and compared with many popular optimization algorithms, including PSO, DE, ABC and their variants. Experimental results show that all the schemes of MBOA are effective for solving most of the benchmark functions, but have different performance on a few benchmark functions. The fourth MBOA scheme has superior performance to the compared methods on many benchmark functions.

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