By Topic

A robust adaptive hybrid genetic simulated annealing algorithm for the global optimization of multimodal functions

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
$33 $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

4 Author(s)
Qiaoling Xu ; Faculty of College of Chemistry and Chemical Engineering, FuZhou University, FuZhou, 350108, P.R. China ; Gongwang Zhang ; Chao Zhao ; Aimin An

In this paper we presented a novel hybrid genetic algorithm for solving NLP problems based on combining the Genetic algorithm and Simulated annealing, together with a local search strategy. The proposed hybrid approach combines the merits of genetic algorithm (GA) with simulated annealing (SA) to construct a more efficient genetic simulated annealing (GSA) algorithm for global search, which could well maintain the population diversity in GA evolution without becoming easily trapped in local optimum. The iterative hill climbing (IHC) method as a local search technique is incorporated into GSA loop to speed up the convergence of the algorithm. In addition, a self-adaptive hybrid mechanism is developed to maintain a tradeoff between the global and local optimizer searching then to efficiently locate quality solution to complex optimization problem. The computational results indicate that the global searching ability and the convergence speed of this hybrid algorithm are significantly improved. Some well-known benchmark functions are utilized to test the applicability of the proposed algorithm.

Published in:

2011 Chinese Control and Decision Conference (CCDC)

Date of Conference:

23-25 May 2011