Optimization Computing Based on Evolution Genetic Algorithm
DOI:
Author:
Affiliation:

Clc Number:

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Deeply analyzed the conventional genetic algorithm and for its shortcomings on numerical optimization, evolution genetic algorithm (EGA) is proposed. EGA makes some improvements on description of genes of chromosome, genetic operators of crossover and mutation, designing of fitness function, selection method on chromosome of candidate solutions and convergence criterion. The optimization results of some functions (including hard Shekel' function) show that EGA has fine ability of global searching and speedy convergence.

    Reference
    Related
    Cited by
Get Citation

陈 明.基于进化遗传算法的优化计算.软件学报,1998,9(11):876-879

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:March 28,1997
  • Revised:October 21,1997
  • Adopted:
  • Online:
  • Published:
You are the firstVisitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-4
Address:4# South Fourth Street, Zhong Guan Cun, Beijing 100190,Postal Code:100190
Phone:010-62562563 Fax:010-62562533 Email:jos@iscas.ac.cn
Technical Support:Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063