东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2006, Vol. 27 ›› Issue (6): 689-693.DOI: -

• 论著 • 上一篇    下一篇

自适应混沌遗传混合算法及其参数敏感性分析

陈炳瑞;杨成祥;冯夏庭;王文杰;   

  1. 东北大学资源与土木工程学院;东北大学资源与土木工程学院;东北大学资源与土木工程学院;东北大学资源与土木工程学院 辽宁沈阳110004;辽宁沈阳110004;辽宁沈阳110004;辽宁沈阳110004
  • 收稿日期:2013-06-23 修回日期:2013-06-23 出版日期:2006-06-15 发布日期:2013-06-23
  • 通讯作者: Chen, B.-R.
  • 作者简介:-
  • 基金资助:
    国家杰出青年科学基金资助项目(50325414);;

Self-adapting chaos-genetic hybrid algorithm and sensitivity analysis of its parameters

Chen, Bing-Rui (1); Yang, Cheng-Xiang (1); Feng, Xia-Ting (1); Wang, Wen-Jie (1)   

  1. (1) School of Resources and Civil Engineering, Northeastern University, Shenyang 110004, China
  • Received:2013-06-23 Revised:2013-06-23 Online:2006-06-15 Published:2013-06-23
  • Contact: Chen, B.-R.
  • About author:-
  • Supported by:
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摘要： 提出自适应搜索空间的混沌遗传混合算法.该方法不同于一般的混沌遗传混合算法,它在遗传进化的过程中根据群体多样性测度引入混沌算子,并从全局搜索空间以随机概率解析出优秀解域,对个体分两个区域进行混沌扰动:优秀解域细搜索和全局解域大扰动.数值仿真表明该算法既加快了收敛速度又提高了收敛精度,解决了传统遗传算法的早熟问题.

关键词: 混沌优化, 遗传算法, 进化计算, 随机优化, 自适应, 敏感性分析

Abstract: Chaos optimization is good at searching local solutions and sensitive to initial value. A self-adapting chaos-genetic hybrid algorithm (SA-CGA) is thus proposed to combine the chaos optimization with TGA (typical genetic algorithm) together. Differing from other conventional chaos-genetic hybrid algorithms, in the algorithm proposed a chaos operator is introduced in the evolution process according to the measure of species diversity and an excellent solvability domain is given in global search space by means of random probability. Then, as a whole, two domains are chaotically disturbed, i.e., searching in the excellent solvability domain in detail together with disturbing greatly the global solvability domain. Numerical simulation shows that the algorithm not only accelerates the convergence rate but improves its accuracy, thus solving the premature problem frequently found in TGA.

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