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微粒群算法在非线性约束优化中的应用 被引量：8

To Solve Nonlinear Constrained Optimization Problems with Particle Swarm Algorithm
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摘要 该文将微粒群算法(PSO)应用于非线性约束优化问题的求解,提出了一种求解非线性约束优化问题的新算法,数值试验表明该算法具有很强的全局寻优能力。 This paper use particle swarm algorithm(PSO)to solve Nonlinear Constrained Optimization Problems ,a new algorithm based on particle swarm algorithm is given and numerical experiences show that the new algorithm has powerful ability of global searching.
作者 张喆 薛任
机构地区 青岛建筑工程学院 河南省南阳市计算中心
出处 《计算机工程与应用》 CSCD 北大核心 2004年第25期90-92,共3页 Computer Engineering and Applications
关键词 微粒群 罚函数 非线性约束优化 particle swarm,penalty function,nonlinear constrained optimization
分类号 TP319 [自动化与计算机技术—计算机软件与理论] O241.7 [理学—计算数学]
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参考文献8

  • 1Fogel D B.An Introduction to Simulated Evolutionary Optimization[J].IEEE Trans on Neural Networks, 1994;5 (1) :3～14
  • 2Joines J A,Houck R C.On the Use of Non-stationary Penalty Functions to Solve Nonlinear Constrained Optimization Problems withGA's[C].In:Proc IEEE Int Conf of Evol Comp,1994:579～585
  • 3Kennedy J,Eberhart R C.Particule Swarm Optimization[C].In:Proc IEEE Int Conf of Neural Networks ,Piscataway ,NJ, 1995: 1942～1948
  • 4Parsopoulos K E.Stretching technique for Obtaining Global Minimizes Through Particle Swarm Optimization[C].In:Proc Particle workshop,Indianpolis ( IN ), USA, 2001: 22～29
  • 5Parsopoulos K E.Initializing the Particle Swarm Optimizer Using the Nonlinear Simplex Method[C].In:Advances in Intelligent Systems,Fuzzy Systems,Evolutionary Computation. WSEAS Press,2002:216～221
  • 6Kennedy J ,Eberhart R C.Swarm Intelligence[M].Morgan Kaufmann,2001
  • 7Parsopoulos K E,Parsopoulos M N.Modification of the particle Swarm Optimizer for Locating All the Global Minima,Artificial Neural Networks and Genetic Algorithm[M].Springer,2001:324～327
  • 8谢晓锋,张文俊,杨之廉.微粒群算法综述[J].控制与决策,2003,18(2):129-134. 被引量：421

二级参考文献34

  • 1[31]Eberhart R, Hu Xiaohui. Human tremor analysis using particle swarm optimization[A]. Proc of the Congress on Evolutionary Computation[C].Washington,1999.1927-1930.
  • 2[32]Yoshida H, Kawata K, Fukuyama Y, et al. A particle swarm optimization for reactive power and voltage control considering voltage security assessment[J]. Trans of the Institute of Electrical Engineers ofJapan,1999,119-B(12):1462-1469.
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  • 5[1]Kennedy J, Eberhart R. Particle swarm optimization[A]. Proc IEEE Int Conf on Neural Networks[C].Perth,1995.1942-1948.
  • 6[2]Eberhart R, Kennedy J. A new optimizer using particle swarm theory[A]. Proc 6th Int Symposium on Micro Machine and Human Science[C].Nagoya,1995.39-43.
  • 7[3]Millonas M M. Swarms Phase Transition and Collective Intelligence[M]. MA: Addison Wesley, 1994.
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  • 9[5]Shi Yuhui, Eberhart R. A modified particle swarm optimizer[A]. Proc IEEE Int Conf on Evolutionary Computation[C].Anchorage,1998.69-73.
  • 10[6]Kennedy J. The particle swarm: Social adaptation of knowledge[A]. Proc IEEE Int Conf on Evolutionary Computation[C].Indiamapolis,1997.303-308.

共引文献420

同被引文献54

引证文献8

二级引证文献63

计算机工程与应用
2004年 第25期

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