Multi-objective Optimization Algorithm based on Magnetotactic Bacterium

In this paper, based on Magnetotactic Bacteria Optimization Algorithm (MBOA), magnetotactic bacterium multi-objective optimization algorithm (MBMOA) is proposed for solving multi-objective optimization problems (MOPs). Magnetotactic bacterium optimization algorithm is a novel random research algorithm which simulate the process of magnetotactic bacteria (MTB) producing magnetosomes(MTS) to regulate cell moment and make the magnetostatic energy reaches the minimum .The algorithm MBOA proposed three operators named by MTS producing, MTS amplification and MTS replacement by imitating the development process of magnetosomes, the adjustment process of magnetosomes moment and the replacement process of magnetosome with worse moment. In MBMOA, MBOA is applied to produce the next population, while non-dominated feasible solutions gained by MBOA are conserved in the archive, then the evaluation method of SPEA2 is adopted to update the archive, at the last through benchmark functions test and classic algorithm comparison, the simulation results show that the MBMOA is feasible and effective for solving multi-objective optimization problems.