[1]李宇中,刘红星,张　胜.猴王遗传算法的改进[J].南京师范大学学报(工程技术版),2004,04(03):053-56.
　LI Yuzhong,LIU Hongxing,ZHANG Shen.Improving Monkey-King Genetic Algorithm[J].Journal of Nanjing Normal University(Engineering and Technology),2004,04(03):053-56.
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猴王遗传算法的改进
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南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

卷:
04卷
期数:
2004年03期
页码:
053-56
栏目:
出版日期:
2004-09-30

文章信息/Info

Title:
Improving Monkey-King Genetic Algorithm
作者:
李宇中1 ; 刘红星1 ; 张　胜2
1. 南京大学电子科学与工程系,江苏南京210093 ;2. 南京师范大学物理科学与技术学院,江苏南京210097
Author(s):
LI Yuzhong 1;  LIU Hongxing 1;  ZHANG Shen 2
1.Department of Electronic Science and Engineering, Nanjing University, Nanjing 210093, China; 2.School of Physical Science and Technology, Nanjing Normal University, Nanjing 210097, China
关键词:
遗传算法;  进化计算;  进化算法;  猴王
Keywords:
genetic algorithm ;  evolutionary computation ;  evolutionary algorithms ;  Monkey-King
分类号:
TP18
摘要:
猴王遗传算法是一种很新颖的遗传算法 ,对其初步的研究已经显示出一定优越性和潜力 .猴王遗传算法尚存在的不足或待改进的地方是 :有些参数要靠人为确定不够方便 ,猴王点附近没有专门的局部寻优机制———影响了整体寻优能力 .针对这些问题 ,对猴王遗传算法进行了改进 ,通过扩大随机个体引进的数量简化了原有的一些参数 ,设计增加了一种局部寻优机制———猴王爬山操作算子 .经大量实验测试 ,改进效果令人满意
Abstract:
Monkey-King Genetic Algorithm is a novel genetic algorithm , and the original research has revealed its some advan tages and potentials. Some aspects to be improved for Monkey-King Genetic Algorithm are : a number of running parameters are inconvenient to be determined by users ,and there is no local searching operator in the area of surrounding the Monkey-King point , so lacking the whole searching ability. Aiming to these two problems , the Monkey-King Genetic Algorithm is improved in this paper. The innovation includes two aspects : one is to enlarge the proportion of the introduced random individuals , thus re ducing the original running parameters , and another is to add a new local searching operator ———Monkey-King up-climbing op erator in the algorithm. A lot of testing experiments show that the improved Monkey-King genetic algorithm is good and satisfac tory.

参考文献/References:

[1 ] 郭晨海,谢俊,刘军,等. 连续非线性规划的猴王遗传算法[J ] . 江苏大学学报(自然科学版) ,2002 ,23 (4) :87- 90.
[2 ] Wolpert D H , Macready W G. No Free lunch theorems for optimization[J ] . IEEE Transactions on Evolutionary Compu tation , 1997 ,1 (2) :62- 87.
[3 ] Kazarlis S A , Papadakis S E , Theocharis J B , et al . Micro genetic Algorithms as Generalized Hill2Climbing Operators for GA Optimization [ J ] . IEEE Transactions on Evolutionary Computation , 2001 ,5 (3) :204- 217.
[4 ] 周明,孙树栋. 遗传算法原理及应用[M] . 北京:国防工业出版社,1999. 125- 128.

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备注/Memo

备注/Memo:
基金项目: 国家自然科学基金资助项目(60275041 ,59905011) .
作者简介: 李宇中(1978 - ) ,硕士研究生,主要从事遗传算法的学习与研究. E-mail :peterlee1978 @163. com
通讯联系人: 刘红星(1968 - ) ,副教授,主要从事智能信息处理的教学与研究. E-mail :njhxliu @nju. edu. cn
更新日期/Last Update: 2013-04-29