By Topic

A gradient-guided niching method in genetic algorithm for solving continuous optimisation problems

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)
Jian Xun Peng ; Sch. of Mech. & Manuf. Eng., Queen''s Univ., Belfast, UK ; Thompson, S. ; Kang Li

A hybrid genetic algorithm, which embeds a gradient-based local search route into a niching genetic algorithm, is proposed for solving continuous optimisation problems. The optimisation algorithm is applied to three nonlinear functions each having up to 100 variables and multi-minima. The test results show that relative to a standard niching algorithm the combination of a gradient-based search and niching improves the searching precision by several orders and the capability for locating the global optimum is significantly improved.

Published in:

Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on  (Volume:4 )

Date of Conference: