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

一种引入单纯形法算子的新颖粒子群算法 被引量：18

A Novel Particle Swarm Algorithm Using the Simplex Method Operator
在线阅读 下载PDF
导出
摘要 提出一种将单纯形法SM与粒子群算法PSO混合的新颖优化算法,在10个著名测试函数上与其他已有算法进行了广泛的比较实验,并研究了不同参数选择对算法的影响.实验结果表明,这种混合算法对传统PSO求解的收敛率和解的质量有较明显的改善,在多峰函数优化问题上优势更突出.算法实现简单,具有很高的可靠性,是一种求解多峰连续函数极值的有效方法.* A novel hybrid simplex method and particle swarm optimization （HSMPSO） algorithm is presented. Comparison experiments with other published methods on 10 benchmark functions are conducted, and the extensive analysis on the effect of different parameters on the algorithm is given. Experimental results indicate that the hybrid method can improve both solution quality and success rates on most selected test functions compared with other alternatives, especially on multimodal functions optimization. Although very easy to implement, this hybrid SM-PSO is an efficient way to locate global optima of continuous multimodal functions.
作者 王芳 邱玉辉
机构地区 西南师范大学智能软件与软件工程实验室
出处 《信息与控制》 CSCD 北大核心 2005年第5期517-522,共6页 Information and Control
基金 国家863计划资助项目(863-511-910-101-01)
关键词 单纯形法 多峰函数优化 粒子群算法 simplex method（SM） multimodal function optimization particle swarm optimization（PSO）
分类号 TP18 [自动化与计算机技术—控制理论与控制工程]
  • 相关文献

参考文献20

  • 1Bonabcau E, Dorigo M, Theraulaz G. Swarm Intelligence: from Natural to Artificial Systems [ M ]. New York: Oxford Press,1999.
  • 2Clerc M, Kennedy J. The particle swarm-explosion, stability, and convergence in a multidimensional complex space [ J ]. IEEETransactions on Evolutionary Computation, 2002, 6 ( 1 ): 58 ～73.
  • 3Yoshida H, Kawata K, FukuyamaY, et al. A particle swarm optimization for reactive power and voltage control considering voltage stability [A]. Proceedings of the International Conference on Intelligent System Application to Power Systems [ C ]. Brazil:Power Systems, 1999. 117 ～ 121.
  • 4Hu X, Eberhart R C, Shi Y H. Engineering optimization with particle swarm [A]. Proceedings of the IEEE Swarm Intelligence Symposium [C]. USA: IEEE, 2003. 53 ～57.
  • 5李爱国.多粒子群协同优化算法[J].复旦学报（自然科学版）,2004,43(5):923-925. 被引量：398
  • 6Kennedy J, Eberhart R C. Particle swarm optimization [ A ]. Proceedings of the IEEE International Conference on Neural Networks [C]. Piscataway, NJ, USA: IEEE Press, 1995. 1942 ～1948.
  • 7Parsopoulos K E, Vrahatis M N. Recent approaches to global optimization problems through particle swarm optimization [ J ].Natural Computing, 2002, 1(2 -3): 235 ～306.
  • 8曾建潮 介婧 崔志华.粒子群算法[M].北京:科学出版社,2004..
  • 9吕振肃,侯志荣.自适应变异的粒子群优化算法[J].电子学报,2004,32(3):416-420. 被引量：453
  • 10Fan S-K S, Liang Y-C, Zahara E. Hybrid simplex search and particle swarm optimization for the global optimization of multimodal functions [ J ]. Engineering Optimization, 2004, 36 ( 4 ):401 ～418.

二级参考文献18

  • 1王小平 曹立明.遗传算法-理论、算法与软件实现[M].陕西西安：西安交通大学出版社,2002.105-107.
  • 2[1]Kennedy J, EberhartRC. Particle swarm optimization [A]. Proceedings of IEEE International Conference on Neural Networks [C]. Piscataway, NJ: IEEE Press, 1995.1942 ～ 1948.
  • 3[2]Eberhart R C, Kennedy J. A new optimizer using particle swarm theory [A]. Proceedings of the Sixth International Symposium on Micro Machine and Human Science [ C]. Nagoya, Japan: IEEE Press, 1995. 39～43.
  • 4[3]Eberhart R C, Simpson P K, Dobbins R W. Computational Intelligence PC Tools [M]. Boston, MA: Academic Press Professional,1996.
  • 5[4]Shi Y, Eberhart R C. A modified particle swarm optimizer [A].Proceedings of the IEEE Congress on Evolutionary Computation [C]. Piscataway, NJ: IEEE Press, 1998.303～308.
  • 6[5]Shi Y, Eberhart R C. Empirical study of particle swarm optimization [A]. Proceedings of the IEEE Congress on Evolutionary Computation [C]. Piscataway, NJ: IEEE Press, 1999.1945 ～ 1950.
  • 7[6]Shi Y, Eberhart R C. Fuzzy adaptive particle swarm optimization [A]. Proceedings of the IEEE Congress on Evolutionary Computation [C]. Seoul, Korea: IEEE Press, 2001. 101 ～106.
  • 8[7]Clerc M, Kennedy J. The particle swarm - explosion, stability,and convergence in a multidimensional complex space [ J ]. IEEE Transactions on Evolutionary Computation, 2002,6( 1 ): 58 ～73.
  • 9[8]Eberhart R C, Shi Y. Comparing inertia weight and constriction factors in particle swarm optimization [ A ]. Proceedings of the IEEE Congress on Evolutionary Computation [ C ]. San Diego,CA: IEEE Press, 2000.84 ～ 88.
  • 10[9]Miranda V, Fonseca N. EPSO-best-of-two-worlds meta-heuristic applied to power system problems [ A ]. Proceedings of the IEEE Congress on Evolutionary Computation [ C ]. Honolulu, Hawaii,USA: IEEE Press, 2002. 1080 ～ 1085.

共引文献900

同被引文献188

引证文献18

二级引证文献146

信息与控制
2005年 第5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