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)


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.


BBO Mean value theory ε-dominance relation Archive strategy 



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).


  1. 1.
    Zheng X, Liu H (2010) A scalable coevolutionary multi-objective particle swarm optimizer. Int J Comput Intell Syst 3(5):590–600Google Scholar
  2. 2.
    Simon D (2008) Biogeography-based optimization. IEEE Trans Evol Comput 12(6):702–713CrossRefGoogle Scholar
  3. 3.
    Haiping MA (2010) An analysis of the equilibrium of migration models for biogeography-based optimization. Inf Sci 180(18):3444–3464CrossRefMATHGoogle Scholar
  4. 4.
    Dawei Du, Simon D, Ergezer M (2009) Biogeography-based optimization combined with evolutionary strategy and immigration refusal systems. In: IEEE International Conference on Man and Cybernetics, pp 997–1002 Google Scholar
  5. 5.
    Gong W, Cai Z, Ling CX (2010) DE/BBO: a hybrid differential evolution with biogeography-based optimization for global numerical optimization. Soft Comput 15(4):645–665CrossRefGoogle Scholar
  6. 6.
    Bhattacharya A, Chattopadhyay PK (2010) Biogeography-based optimization for different economic load dispatch problems. IEEE Trans Power Syst 25(2):1064–1077CrossRefGoogle Scholar
  7. 7.
    Zhidan XU, Hongwei MO (2012) Improvement for migration operator in biogeography-based optimization algorithm. Pattern Recognit Artif Intell 25(3):544–549 (In Chinese with English Abstract)Google Scholar
  8. 8.
    Costa E, Silva MA, Coelho LS, Lebensztajn L (2012) Multiobjective biogeography-based optimization based on predator-prey approach. IEEE Trans Magn 48(2):951–954CrossRefGoogle Scholar
  9. 9.
    Jamuna K, Swarup KS (2012) Multi-objective biogeography based optimization for optimal PMU placement. Appl Soft Comput 12(5):1503–1510CrossRefGoogle Scholar
  10. 10.
    Zheng X, Liu H (2009) A hybrid vertical mutation and self-adaptation based MOPSO. Comput Math Appl 57(11):2030–2038Google Scholar
  11. 11.
    Deb K, Pratap A, Agarwal S et al (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6(2):182–197CrossRefGoogle Scholar
  12. 12.
    Zhang M, Luo W, Wang X (2009) A normal distribution crossover for ε-MOEA. J Software 20(2):305–314. (In Chinese with English Abstract)Google Scholar
  13. 13.
    Chen M, Zhang C, Luo C (2009) Adaptive evolutionary particle swarm algorithm for multi-objective optimization. J Syst Simul 21(22):7061–7065 (In Chinese with English Abstract)Google Scholar

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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