文摘
In current years, Biogeography-Based Optimization (BBO), a novel Evolutionary Algorithm (EA), has drawn a lot of attention due to its dramatic performance. In our previous work, BBO’s migration models for single-objective problem (SOP) have been investigated to reveal their effects to algorithm’s performance. However to date, there is a few investigation about migration models for Multi-Objective Problems (MOPs) which are common in practice though more difficult. To make BBO competitive in dealing with MOPs, migration models of BBO are explored and exploited in this paper. One contribution of our work is that we propose Multi-objective BBO (MOBBO). By comparing MOBBO with other popular MOEAs, this algorithm is competent to handle MOPs. Besides, we present and compare six principal migration models. In comparisons, we find that Trapezoidal Migration Model performs well for MOPs, while its performance is inferior to other migration models for SOPs. Besides, Quadratic Migration Model’s performance for MOPs is worse, while it has a good performance to solve SOPs. These demonstrate that the conclusion to evaluate migration models for SOPs does not hold for MOPs, so another contribution in this paper is that we reevaluate migration models for MOPs in an empirical way, which is helpful to design migration models for MOBBO.
