By Topic

Minimum Spanning Tree Problem Research Based on Genetic Algorithm

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

2 Author(s)
Hong Liu ; Coll. of Inf. Eng., Zhejiang Univ. of Technol., Hangzhou, China ; Gengui Zhou

Minimum spanning tree (MST) problem is of high importance in network optimization, but it is also difficult for the traditional network optimization technique to deal with. In this paper, self-adaptive genetic algorithm (GA) approach is developed to deal with this problem. Without neglecting its network topology, the proposed method adopts the Pru¿fer number as the tree encoding and self-adaptation is used to enable strategy parameters to evolve along with the evolutionary process. Compared with the existing algorithm, the numerical analysis shows the efficiency and effectiveness of such self-adaptive GA approach on the MST problem.

Published in:

Computational Intelligence and Design, 2009. ISCID '09. Second International Symposium on  (Volume:2 )

Date of Conference:

12-14 Dec. 2009