Volume 39 Issue 4
Apr.  2013
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Liu Baoning, Zhang Weiguo, Li Guangwen, et al. Improved multi-objective particle swarm optimization algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics, 2013, 39(4): 458-462,473. (in Chinese)
Citation: Liu Baoning, Zhang Weiguo, Li Guangwen, et al. Improved multi-objective particle swarm optimization algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics, 2013, 39(4): 458-462,473. (in Chinese)

Improved multi-objective particle swarm optimization algorithm

  • Received Date: 26 Apr 2012
  • Publish Date: 30 Apr 2013
  • In order to enhance the convergence and diversity of multi-objective particle swarm optimization algorithm, an improved multi-objective particle swarm optimization algorithm was proposed. The Kent mapping was used to initialize the population, and the target space was divided into several fan-shaped regions evenly. A new diversity and convergence criteria was proposed to select the optimal solutions. An improved particle swarm update formula was used for global search. The clustering algorithm was used to analyze the angles between external population and the axis, and ensure the diversity of external population. Compared with the multi-objective particle swarm optimization algorithm and the nondominated sorting genetic algorithm II, the experiment of benchmark functions simulation verifies the effectiveness of the improved algorithm.

     

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  • [1]
    Kennedy J,Eberhant R C.Particle swarm optimization[C]// Proc of the IEEE International Conference on Neural Networks.Piscataway,NJ:IEEE Service Center,1995:1942-1948
    [2]
    Mostaghim S,T eich J.The role of ε-dominance in multi-objective particle swarm optimization method[C]// Proc of the 2003 Congress on Evolutionary Computation.Canberra:IEEE,2003:1764-1771
    [3]
    Coello C A,Lechuga M S.MOPSO:a proposal for multiple objective particle swarm optimization[C]// Proceedings of the Congress on Evolutionary Computation.Piscataway:IEEE,Service Center,2002:1051-1056
    [4]
    Leong W F,Yen G G.Dynamic swarms in PSO-based multiobjective optimization[C]// IEEE Congress on Evolutionary Computation.Singapore:IEEE,2007:3172-3179
    [5]
    Leong W F,Yen G G.Dynamic population size in PSO-based multiobjective optimization[C]// IEEE Congress on Evolutionary Computation.Vancouver:IEEE,2006:1718-1725
    [6]
    Balling R.The maximin fitness function multi-objective city and regional planning[C]//Proc of the 2nd Int Conf on Evolutionary Multi-criterion Optimization.Faro:Springer,2003:1-15
    [7]
    徐明,沈希,马龙华,等.一种多目标粒子群改进算法的研究[J].控制与决策,2009,24(11):1713-1718
    Xu Ming,Shen Xi,Ma Longhua,et al.Research on modified multi-objective particle swarm optimization[J].Control and Decision,2009,24(11):1713-1718(in Chinese)
    [8]
    雷德明,严新平.多目标智能优化算法及其应用[M].北京:科学出版社,2009:106-107
    Lei Deming,Yan Xinping.Multi-objective intelligent optimization algorithm and its application[M].Beijing:Science Press,2009:106-107(in Chinese)
    [9]
    陈增强,周茜,袁著祉.基于Kent映射的数字喷泉编解码方法研究[J].系统科学与数学,2011,31(6):731-741
    Chen Zengqiang,Zhou Qian,Yuan Zhuzhi.Research on the digital fountain codes and decodes algorithm based upon kent mapping[J].Journal of System Science and Mathematical Science,2011,31(6):731-741(in Chinese)
    [10]
    刘丽琴,张学良,谢黎明,等.基于动态聚集距离的多目标粒子群优化算法及应用[J].农业机械学报,2010,41(3):189-194
    Liu Liqin,Zhang Xueliang,Xie Liming,et al.Multi-objective particle swarm optimization algorithm based on dynamic crowding distance and its application[J].Transaction of the Chinese Society for Agricultural Machinery,2010,41(3):189-194(in Chinese)
    [11]
    Zitzler E,Deb K,Thiele L.Comparison of multi-objective evolutionary algorithms:Empirical results[C]// Proc of the 2005 Congress on Evolutionary Multi-criterion Optimization.Berlin:Springer-Verlag,2005:165-175
    [12]
    吴森堂,费玉华.飞行控制系统[M].北京:北京航空航天大学出版社,2006:262-273
    Wu Sentang,Fei Yuhua.Flight control system[M].Beijing:Beihang University Press,2006:262-275(in Chinese)
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