期刊文献+

一种改进的进化策略研究 被引量:2

Study on Improved Evolutionary Strategy
下载PDF
导出
摘要 提出了一种新的进化策略,基于物种保护的混合变异算子进化策略,它混合了四种不同的变异算子(Gaussian、Cauchy、Levy和单点(Single Point)),并结合了使局部优化不被陷入困境的物种保护技术.使用国际通用标准函数来测试这种新算法,仿真的结果表明了基于物种保护的混合变异算子进化策略优于任何一种纯策略的进化策略. In this paper,an example of such strategies is introduced which employs four different mutation strategies:Gaussian,Cauchy,Levy,single-point.It also combines with the technique of species conservation to prevent the evolutionary strategy from being trapped in local optima.This mixed strategy has been tested on benchmark functions.The simulation results show that the mixed mutation strategy is superior to any pure mutation strategy.
出处 《微电子学与计算机》 CSCD 北大核心 2009年第2期58-61,共4页 Microelectronics & Computer
基金 黑龙江省自然科学基金项目(F200605) 黑龙江省教育厅海外学人资助项目(1153h21)
关键词 进化策略 混合变异 物种保护 evolutionary strategy mixed mutation species conservation
  • 相关文献

参考文献3

二级参考文献38

  • 1Charnes A, Cooper W W. Management Models and Industrial Applications of Linear Programming, Volume 1. New York:John Wiley, 1961.
  • 2Ijiri Y. Management Goals and Accounting for Control. Amsterdan: North Holland, 1965.
  • 3Hajela P, Lin C Y. Genetic search strategies in multicriterion optimal design. Structural Optimization, 1992, 4 : 99 - 107.
  • 4Chen Y L, Liu C C. Multiobjective VAR planning using the goal-attainment method, IEE Proceedings on Generation,Transmission and Distribution, 1994,141 (3) :227 -232.
  • 5Coello C A C, Christiansen A D, Aguirre A H. Using a new GA- based multiobjective optimization technique for the design of robot arms. Robotica, 1998,16:401-414.
  • 6Fujita K, Hirokawa N, Akagi S, Kitamura S, Yokohata H.Multi-objective optimal design of automotive engine using genetic algorithm. In: Proceedings of DETC'98-ASME Design Engineering Technical Conferences, 1998.
  • 7Cvetkovic D, Parmee I C. Genetic algorithm-based multi-objective optimization and conceptual engineering design, Washington DC, 1999. 29-36.
  • 8Zitzler E, Thiele L. Multiobjective optimization using evolutionary algorithms-a comparative case study. In: Eiben A E.Back T, Schoenauer M, Schwefel H P eds. Parallel Problem Solving from Nature, Berlin, Germany: Springer, 1998. 292-301.
  • 9Knowles J, Corne D. The Pareto archived evolution strategy:A new baseline algorithm for multiobjective optimization. In:Proceedings of the 1999 Congress on Evolutionary Computation, Washington DC, 1999. 98-105.
  • 10Coello C A C, Christiansen A D. Two new GA- based methods for multiobjective optimization. Civil Engineering Systems,1998, 15(3) :207-243.

共引文献134

同被引文献10

引证文献2

二级引证文献6

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