首页 | 本学科首页   官方微博 | 高级检索  
     

基于不动点理论的改进遗传算法及其应用
引用本文:李群,高瑞贞,张京军.基于不动点理论的改进遗传算法及其应用[J].河北工程大学学报,2013,30(3):67-70.
作者姓名:李群  高瑞贞  张京军
作者单位:河北工程大学
基金项目:国家自然科学基金项目(面上项目,重点项目,重大项目)
摘    要:针对遗传算法的遗传效率问题,引入不动点理论的“剖分—标号—剖分”思想,通过寻找全标单纯形来对最优解进行定位,对全标单纯形再次剖分,寻找其内部的全标单纯形,使最优解得范围进一步缩小。遗传算法按相对适应度大小随机选取全标单纯形内的点作为初始化群体,极大地提高了遗传算法的效率。将遗传变异区间化,锁定在全标单纯形内或附近单纯形,使得最优解的精确度也得到极大地提高。

关 键 词:遗传算法  不动点  K1  剖分  全标单纯形  整数标号
收稿时间:2013/4/24 0:00:00

Improved genetic algorithm based on fixed point theory and its application in multi-dimensional space
Authors:LI Qun  GAO Rui-zhen and ZHANG Jing-jun
Affiliation:School of Information Science and Electrical Engineering, Hebei University of Engineering;School of Information Science and Electrical Engineering, Hebei University of Engineering;School of Information Science and Electrical Engineering, Hebei University of Engineering
Abstract:The fixed point theory of the "split - label - split" idea is introduced into the genetic algorithms to slove genetic efficiency , locking the optimal solution looking for completely labeled simplexes, finding their internal completely labeled simplexes in the resubdivision of simplexes in the previous step make the optimal solution regions further reduced. Genetic Algorithms randomly selecte points in the completely labeled simplexes as the initial group in the relative size of the fitness,which greatly improved the efficiency of genetic algorithm. Genetic variation occurred in completely labeled simplexes or near them,which makes the precision of the optimal solution greatly improved.
Keywords:Genetic algorithm  Fixed point  completely labeled simplexes  Integer label
点击此处可从《河北工程大学学报》浏览原始摘要信息
点击此处可从《河北工程大学学报》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号