期刊名称：International Journal of Hybrid Information Technology
印刷版ISSN：1738-9968
出版年度：2014
卷号：7
期号：3
页码：225-234
DOI：10.14257/ijhit.2014.7.3.22
出版社：SERSC
摘要：Biogeography-based optimization (BBO) has shown excellent exploitation ability of the population information for simple-objective optimization problem. But if BBO is directly applied in multi-objective optimization problems (MOPs), optimal solution set gained by BBO has worse diversity and distribution. To overcome these shortcomings, a chaos migration operator is put forwards to improve the diversity of the population. And then based on the new chaos migration operator, Chaos biogeography multi-objective optimization algorithm (CBBMO) is proposed for MOPs. In CBBMO, the chaos migration operator and original mutation operator of BBO are applied to produce the next generation population. The archive is used to conserve the Pareto optimal solutions. The experiment results show that the proposed algorithm CBBMO is feasible and effective for MOPs.
