全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

一种改进的多目标粒子群优化算法

Full-Text   Cite this paper   Add to My Lib

Abstract:

为了增强多目标粒子群优化算法的收敛性与多样性,提出一种改进的多目标粒子群算法.采用Kent映射对种群进行初始化,并将目标空间均匀划分为若干扇形区域;基于一种新的多样性和收敛性判定标准,选取合适的收敛性最优解和多样性最优解,并提出一种改进的粒子群更新公式进行全局搜索;采用聚类算法对外部种群与坐标轴夹角进行分析,维护外部种群.通过标准测试函数的仿真实验,与多目标优化算法基本MOPSO(Multi-objectiveParticleSwarmOptimizationAlgorithm)和NSGA-II(NondominatedSortingGeneticAlgorithmII)进行对比,结果表明了该改进算法的有效性.

References

[1]  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,2006:262-273Wu Sentang,Fei Yuhua.Flight control system[M].Beijing:Beihang University Press,2006:262-275(in Chinese)
[2]  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):1713-1718Xu 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)
[3]  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,2009:106-107Lei Deming,Yan Xinping.Multi-objective intelligent optimization algorithm and its application[M].Beijing:Science Press,2009:106-107(in Chinese)
[4]  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,2006:262-273Wu Sentang,Fei Yuhua.Flight control system[M].Beijing:Beihang University Press,2006:262-275(in Chinese)
[5]  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
[6]  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
[7]  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
[8]  Leong W F,Yen G G.Dynamic swarms in PSO-based multiobjective optimization[C]// IEEE Congress on Evolutionary Computation.Singapore:IEEE,2007:3172-3179
[9]  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
[10]  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
[11]  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):731-741Chen 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)
[12]  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):189-194Liu 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)
[13]  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

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133