IEEE.org| IEEE Xplore Digital Library| IEEE Standards| IEEE Spectrum| More Sites

Cart (Loading....) | Create Account | 

Close category search window
Author Searchbeta |  Advanced Search  |  Preferences |  Search Tips  |  More Search Options  
 
Browse Conference Publications > Systems, Man and Cybernetics, ... Help

Convergence and calculation efficiency analysis of abstract model of nonlinear genetic algorithm based on function group

Full Text Sign-In or Purchase

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing! close button
puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Cui Zhi-Hua ; Div. of Syst. & Simulation & Comput. Application, Taiyuan Heavy Machinery Inst., China ; Zeng Jian-chao ; Xu Yu-Bin

Through mechanism analysis of genetic algorithm (GAs), every genetic operator of SGA and their combination action can be considered as linear transformations to the corresponding individuals. By modifying the traditional genetic operators, the nonlinear genetic algorithm (NGA) is introduced. In this paper, abstract model of NGA based on function group is discussed in which every function is selected with some probability, and if the function group is correctly selected, then the algorithm can be convergent to global optimal within every given generation number. With this technique the premature convergence and calculation efficiency may be solved.

Published in:
Systems, Man and Cybernetics, 2003. IEEE International Conference on  (Volume:5 )

Date of Conference: 5-8 Oct. 2003

Page(s):
4655 - 4659 vol.5
ISSN :
1062-922X
Print ISBN:
0-7803-7952-7
INSPEC Accession Number:
7914530
Digital Object Identifier :
10.1109/ICSMC.2003.1245718
Product Type:
Conference Publications

IEEE Account

Purchase Details

Profile Information

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2013 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.