Magnetotactic bacteria optimization algorithm based on best-target scheme

Magnetotactic bacteria optimization algorithm (MBOA) is a new optimization algorithm inspired by 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. The function of magnetoaerotaxis is to enhance the ability of magnetotactic bacteria to sense oxygen concentration and enable them to more efficiently locate favorable environments. In this paper, an improved MBOA based on best individual´s moments is proposed. It generates candidate solutions based on the interaction energy of cells and can solve the optimization problems by regulating magnetosome moments based on the local best cell´s moments with some other cells to balance the local search and global search. Its performance is tested on thirteen standard function problems and compared with one of the most popular optimization algorithm DE and its variants. Experiment results show that the MBOA is very effective in optimization problems and has superior performance to the compared methods on many benchmark functions.