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A Multi-objective Biogeography-Based Optimization with Mean Value Migration Operator

  • Kai-ge Gao
  • Xiang-wei Zheng
  • Xiao-guang Wang
  • Chi-zhu Ma
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 269)

Abstract:

Considering its successful application in solving discrete single objective problems, biogeography-based optimization (BBO) is considered as a new promising intelligent algorithm. Therefore, many studies are conducted to apply it to solve multi-objective optimization problems (MOPs). However, these improved BBOs are not always effective because of the complexity of MOPs. A multi-objective biogeography-based algorithm with mean value migration operator named MVBBO is proposed in this paper. In MVBBO, mean value theory and new boundary constraint rule are adopted to extend the range of feasible domain. Meanwhile, mutation operator and ε-dominance-based archive strategy are employed to achieve better convergence and diversity. Simulation on benchmark functions shows that the proposed MVBBO’s final Pareto solution set is better than NSGA-II and other improved multi-objective BBOs in convergence and distribution of Pareto solutions.

Keywords:

BBO Mean value theory ε-dominance relation Archive strategy 

Notes

Acknowledgments

We are grateful for the support of the Promotive Research Fund for Excellent Young and Middle-aged Scientists of Shandong Province (BS2010DX033) and a Project of Shandong Province Higher Educational Science and Technology Program (J10LG08).

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Kai-ge Gao
    • 1
    • 2
  • Xiang-wei Zheng
    • 1
  • Xiao-guang Wang
    • 1
  • Chi-zhu Ma
    • 3
  1. 1.School of Information Science and EngineeringShandong Normal UniversityJinanChina
  2. 2.Shandong Provincial Key Laboratory for Distributed Computer Software Novel TechnologyJinanChina
  3. 3.School of CommunicationShandong Normal UniversityJinanChina

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