期刊文献+

基于主从结构的遗传算法研究 被引量:3

Study Genetic Algorithm Based on Master-Slave Structure
下载PDF
导出
摘要 提出一种主-从结构的遗传算法。算法中,主级为全局搜索染色体;从级为局部邻域搜索染色体。通过主-从协调机制和从级转换函数设计,使算法不依赖复杂的编码方式和复杂的遗传算子进行全局精确搜索。通过仿真和比较实验,验证了算法的有效性。 A genetic algorithm with master-slave structure was proposed. The algorithm was formulated in a form of hierarchical structure. The global search was performed at the master level, while the local search was carried out at the slave level. Through the harmonizing mechanism between master and slave level, and special translation function designed for the slave level, the algorithm could execute global exact search without relying on complex coring and complex genetic operators. The simulation and results from comparison with other algorithms demonstrate the effectiveness of the proposed algorithm.
出处 《系统仿真学报》 EI CAS CSCD 北大核心 2007年第6期1209-1211,共3页 Journal of System Simulation
关键词 遗传算法 算法结构 转换函数 优化 genetic algorithm algorithm structure translation function optimization
  • 相关文献

参考文献6

  • 1Goldberg D E.Genetic Algorithms in Search,Optimization and Machine Learning[M].New York:Addison-Wesley,1989,1-83.
  • 2Yao Jie,Kharma Nawwaf,Grogono Peter.BMPGA:a bi-objective multi-population genetic algorithm for multi-modal function optimization[C]// Evolutionary Computation,The 2005 IEEE Congress on:2005,816-823.
  • 3刘洪杰,王秀峰.多峰搜索的自适应遗传算法[J].控制理论与应用,2004,21(2):302-304. 被引量:23
  • 4郑朝晖,张焱,裘聿皇.一种基于复数编码的遗传算法[J].控制理论与应用,2003,20(1):97-100. 被引量:11
  • 5陈小平,于盛林.实数遗传算法交叉策略的改进[J].电子学报,2003,31(1):71-74. 被引量:52
  • 6Malay K Pakhira,Rajat K De.Function optimization using a pipelined genetic algorithm[C]// Intelligent Sensors,Sensor Networks and Information Processing Conference,2004,Proceedings of the 2004:253-257.

二级参考文献11

  • 1MICHALEWICZ Z. Genetic Algorithms + Data Structures = Evolution Programs [M]. Berlin, Heidelberg, New York: Springer-Verlag, 1994.
  • 2WANG Xiufeng, ELBULUK M E. The application of genetic algorithm with neural networks to the induction machines modeling [J].System Analysis Modeling Simulation, 1998,31:93- 105.
  • 3HOLLAND J H. Adaptation in Natural and Artificial System: An Introduction Analysis with Applications to Biology, Control and Artificial Intelligence [M]. Michigan, USA: The University of Michigan Press, 1975.
  • 4GOLDBERG D E, RICHARDSON J. Genetic algorithms with sharing for multimodel function optimization [C]//Proc of the Second lnt Confon Genetic Algorithms: July 28 - 31, 1987 at the Massachusetts Institute of Technology. Massachusetts, USA: The Massachusetts Institute of Technology Press, 1987:41 -49.
  • 5WILLIAM M. Spears, simple subpopulation schemes [C]//Proc of the Third Annual Conference on Evolutionary Programming, Feb. 24- 26, 1994 at San Diego, California, USA. Singapore: World Scientific, 1994:296 - 307.
  • 6刘洪杰.[D].天津:南开大学,2002.
  • 7CASASENT D, NATARAJAN S. A classifier neural network with complex-valued weights and square-law nonlinearities [J]. Neural Networks, 1995,8(6) :989 -998.
  • 8CHEN Guoliang, WANG Xifa, ZHUANG Zhenquan,et al. Genetic Algorithms and the Applications [ M]. Beijing: People's Posts & Telecommunications Publishing House, 1996 (in Chinese).
  • 9PAN Zhengjun, KANG Lishan, CHEN Yuping. Evolutionary Computing [M]. Beijing: Tsinghua University Press, 1998 ( in Chinese).
  • 10ACKLEY D. A Connectionist Machine for Genetic Hillclimbing [M].Boston: Kluwer Academic Publishers. 1987.

共引文献83

同被引文献28

引证文献3

二级引证文献8

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