Abstract In original biogeography-based optimization (BBO), the migration and mutation operators are applied to evolve the population. BBO is often used to solve single-objective optimization problems. When the original migration operator of BBO is applied to solve continuous multi-objective optimization problems, the diversity of the population is decreased sharply. In this paper, the migration operator of BBO is developed and the perturbation factor is introduced to increase the diversity of the population. Thus, a biogeography-based multi-objective evolutionary algorithm (BBMOEA) is proposed. Compared with the algorithm under the action of the original migration operator on benchmark test problems, the simulation results illustrate the effectiveness and efficiency of the developed migration operator. Meanwhile, compared with SPEA2 and NSGA-Ⅱ, the experimental results show that the solution set gained by algorithm BBMOEA has good convergence and even distribution.
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2012, Vol. 25 
