期刊文献+

基于数论的总体优化随机搜索算法 被引量:3

GLOBAL OPTIMIZATION RANDOM SEARCHIN G ALGORITHM BASED ON NUMBER-THEORY
下载PDF
导出
摘要 本文研究了多峰函数的总体优化问题.提出了基于数论的总体优化随机搜索算法,证明了算法依概率1收敛到总体极值点,并给出了计算示例. In this paper, the global optimization problems of the multimodal function are studied. A new global optimization random searching algorithm based on number-theory is proposed. Practice makcs out that is an effective algorithm. The correlative theory analysis is made and calculating examples are given.
出处 《数学杂志》 CSCD 北大核心 2006年第1期75-82,共8页 Journal of Mathematics
基金 国家自然科学基金资助项目(70171016) 亚大运筹中心资助项目 中国科学院管理决策与信息系统开放研究室资助项目.
关键词 总体优化 随机搜索 数论 global optimizatiom random searching number-theoretic.
  • 相关文献

参考文献13

  • 1Floudus C.A.,P.H.Pardalos,Recent Advances in Global Optimization,Princeton Series in Computer Science Princeton[M].NJ,Princeton University Press,1992.
  • 2Evtushenko Y.G.,Numerical Methods for Finding Global Extreme Case of a Uniform Mesh[J].USSK Computational Mathematics and Mathematical Physics,1971,11 (1):38-54.
  • 3Hansen E.R.,Global Optimization Using Interval Analysis,the One-dimensional Case [J] J.of Optimization Theory and Applications,1979,29 (2):331-344.
  • 4Hansen E.R.,Global Optimization Using Interval Analysis,the Multi-dimensional Case[J].Numerische Mathematic,1980,34,fasc.2:247-270.
  • 5Renpu G.E..A Filled Function Method for Finding A Global Minimized of a Function of Several variables[J].Mathematical Programming,1990,46(2):191-204.
  • 6Ge R.P.,and Din Y.E.,A Class of Filled Functions for Finding Global Minimizes of A Function of Several Variables[J].J.of Optimization Theory and Applications,1987,54(2):241-252.
  • 7章祥荪.总体极值确定型方法研究的进展.运筹学杂志,1984,3(2):1-13.
  • 8Fang K.T.(方开泰),and Wang Y.(王元),Number-theoretic,Methods in Statistics[M].United Kingdom:Chapman and Hall,1994.
  • 9郑权 张连生.罚函数与带不等式约束的总体极值问题[J].计算数学,1980,2(2):146-153.
  • 10郑权 蒋百川 庄松林.一个求总体极值的方法[J].应用数学学报,1978,1(2):161-174.

同被引文献22

  • 1张晓清,张建科,方敏.多峰搜索的动态微粒群算法[J].计算机应用,2005,25(11):2668-2670. 被引量:9
  • 2刘飞,窦毅芳,张为华.数论网格法在极大似然估计中的应用[J].系统仿真学报,2006,18(9):2534-2536. 被引量:4
  • 3Zixing Cai, Yong Wang. A Multiobjective Optimization-Based Evolutionary Algorithm for Conslrained Optimization [J]. IEEE Trans. on Evolution Computation (S 1089-778X), 2006, 10(6): 658-675.
  • 4Deb K, Agrawal S. A niched-penalty approach for const(ained handling in genetic algorithms [C]// Montana D, Ed. Proceedings of the ICANNGA-99. Portoroz, Slovenia, 1999: 243-239.
  • 5Leung Y W, Wang Y. An orthogonal genetic algorithm with quantization for global numerical optimization [J]. IEEE Trans.on Evolution Computation (S1089-778X), 2001, 5(1): 53-62.
  • 6Zeng Sanyou, Kang Lishan, Ding Lixin. An Orthogonal Multi-objective Evolutionary Algorithm for Multi-objective Optimization Problems with Constraints [J]. Evolutionary Computation (S1063-6560), 2004, 12(1): 77-98.
  • 7Muhlenbein H, Schlierkamp-Voosen D. Predictive models for the breeder genetic algorithm I: continuous parameter optimization [J]. Evolutionary Computation (S1063-6560), 1993, 1(1): 25-49.
  • 8Farmani R, Wright J A. Self-adaptive fitness formulation for constrained optimization [J]. IEEE Trans. on Evolution Computation (S1089-778X), 2003, 7(5): 445-455.
  • 9Efren Mezura-Montes, Carlos A CoeUo Coello. A Simple Multimembered Evolution Strategy to Solve Constrained Optimization Problems [J]. IEEE Trans. on Evolution Computation (S1089-778X), 2005, 9(1): 001-017.
  • 10Benzi R, Sutera S, Vulpiani A. The mechanism of stochastic resonance[J]. Phys. A, 1981,14: L453-L457.

引证文献3

二级引证文献7

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