期刊文献+
任意字段
题名或关键词
题名
关键词
文摘
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息

一种非线性约束优化的微粒群新算法 被引量：8

A new algorithm for solving nonlinear constrained optimization problems with particle swarm optimizer
下载PDF
导出
摘要 通过对标准微粒群算法(PSO)改进,采用动态罚函数的方法,提出了一种求解非线性约束优化问题的新算法.由于使用了一种新的适应度函数,该算法具有很强的全局寻优能力. This Paper presents a new evolutionary algorithm for solving nonlinear constrained optimization problems based on particle swarm optimizer（PSO）. Dynamic penalty function is adopted in this algorithm to transform the constrained optimization problems into unconstrained optimization problems. Because a new fitness function which is able to get global minimum has been proposed, the new algorithm has shown its powerful ability for solving nonlinear constrained optimization problems in the benchmark tests.
作者 张喆 孟庆春 薛任 高云 刘敏 张淑军
机构地区 中国海洋大学计算机系 南阳市计算机中心
出处 《哈尔滨工业大学学报》 EI CAS CSCD 北大核心 2006年第10期1716-1718,共3页 Journal of Harbin Institute of Technology
基金 国家自然科学基金资助项目(60374031)
关键词 全局寻优 微粒群 动态罚函数 适应度函数 非线性约束优化 global optimization particle swarm optimizer dynamic penalty function fitness function non-linear constrained optimization
分类号 TP301.6 [自动化与计算机技术—计算机系统结构]
  • 相关文献

参考文献9

  • 1JONIES J A,HOUCK R C.On the Use of Non-stationary Penalty Functions to Solve Nonlinear Constrained Optimization Problems with GA' s[A].Proc IEEE Int of Evol Comp[C].1994.
  • 2Van den Bergh F.Analysis of Particle Swarm Optimizers[D].University of Pretoria,2001.
  • 3Fogel D Ban.Introduction to Simulated Evolutionary Optimization[J].IEEE Trans on Neural Networks,1994 ;5(1):3-14.
  • 4KENNEDY J,ELBERHART R C.Particule Swarm Optimization[A].Proc IEEE Int Conf of Netral Networks[C].Piscataway,NJ,1995:1942-1948.
  • 5PARSOPOULOS K E.Stretching Technque for Obtaining Global Minimizes Through Particle Swarm Optimization[A].Proc Particle Workshop,Indianpolis (IN)[C].2001.
  • 6PARSOPOULOS K E.Initializing the Particles Swarm Optimizer Using the Nonlinear Simplex Method[A].Advanced in Intelligent Systems,Fuzzy System,Evolutionary Computation[C].WSEAS Press,2002.
  • 7PARSOPOULUS K E,PARSOPOULUS 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.
  • 8KENNEDY J,EBERHART R C.Swarm Intelligence[M].Morgan Kaufmann 2001.
  • 9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：422

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.
  • 3[33]Eberhart R, Shi Yuhui. Tracking and optimizing dynamic systems with particle swarms[A]. Proc IEEE Int Conf on Evolutionary Computation[C].Hawaii,2001.94-100.
  • 4[34]Prigogine I. Order through Fluctuation: Self-organization and Social System[M]. London: Addison-Wesley,1976.
  • 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.
  • 8[4]Wilson E O. Sociobiology: The New Synthesis[M]. MA: Belknap Press,1975.
  • 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421

同被引文献66

引证文献8

二级引证文献23

哈尔滨工业大学学报
2006年 第10期

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部