Magnetotactic bacteria optimization algorithm based on best-rand scheme

Magnetotactic bacteria optimization algorithm (MBOA) is a kind of optimization algorithm inspired by the characteristics of magnetotactic bacteria(MTB). They have chains consisting of micro magnetic particles called magnetosomes inside their bodies. These magnetic chains make MTB have magnetotaxis that make them orient and swim along geomagnetic field lines. The original MBOA mimics the interaction energy between magnetosomes chains to obtain moments for solving problems. But its performance is mainly update to operation of candidate solutions replacement with randomly generated cells. In this paper, an improved MBOA is proposed. It regulates the moments based on the information exchange between best individual´s moments and some randomly one. It is called best-rand scheme. The performance of proposed algorithm is tested on twelve standard function problems and compared with some popular optimization algorithms, including variants of DE, ABC. Experiment results show that the improved algorithm is very effective in optimization problems and has superior performance to the compared methods on many benchmark functions.