Magnetotactic Bacteria Optimization Algorithm Based on Moment Interaction Energy

In this paper, an improved magnetotactic bacteria optimization algorithm (IMBOA) is proposed to solve unconstrained optimization problems. IMBOA uses an archive to keep some better solutions in order to guide the moving of the whole population in each generation. And it uses a kind of efficient interaction energy to enhance diversity of the population for encouraging broader exploration. The proposed algorithm is compared with some relative optimization algorithms on the CEC 2013 real-parameter optimization benchmark functions. Experimental results show that the proposed algorithm IMBOA has better performance than the compared algorithms on most of the benchmark problems.