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一种新的改进遗传算法
引用本文:欧阳森,王建华,耿英三,宋政湘,陈德桂. 一种新的改进遗传算法[J]. 计算机工程与应用, 2003, 39(11): 13-15
作者姓名:欧阳森  王建华  耿英三  宋政湘  陈德桂
作者单位:西安交通大学电器教研室,西安,710049
基金项目:2000年国家高技术产业发展项目计划(编号:计高技犤2000犦1883号)
摘    要:该文提出了一种新的改进遗传算法,通过设计与进化代数相关的交叉概率及与个体适应度相关的自适应变异概率,并采取避免近亲繁殖的交叉手段等方法,来改善遗传算法的质量,提高其搜索能力和收敛速度。计算结果表明该算法达到了预期效果。

关 键 词:遗传算法  交叉  自适应变异率  收敛性
文章编号:1002-8331-(2003)11-0013-03
修稿时间:2002-12-01

A New Improved Genetic Algorithm
Ouyang Sen Wang Jianhua Geng Yingsan Song Zhengxiang Chen Degui. A New Improved Genetic Algorithm[J]. Computer Engineering and Applications, 2003, 39(11): 13-15
Authors:Ouyang Sen Wang Jianhua Geng Yingsan Song Zhengxiang Chen Degui
Abstract:A New Improved Genetic Algorithm(NIGA)is proposed in this paper.In the NIGA,a new probability algo-rithm of crossover depending on the number generations,and a new probability algorithm of mutation depending on the fitness value are designed.Others,an incest preventing crossover strategy is proposed also.All this methods can help to enhance the capability of the genetic algorithm,and solve the main conflict of the convergence speed with the global astringency.Finally,the validity of the proposed method is verified by the results of the simulation.
Keywords:Genetic algorithm  Crossover  Adaptive mutation probability  Convergence
本文献已被 CNKI 维普 万方数据 等数据库收录!
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