Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Liu, Liyang* | Wu, Junji | Meng, Shaoliang
Affiliations: School of Energy and Power Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu, China
Correspondence: [*] Corresponding author: Liyang Liu, School of Energy and Power Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu, China. E-mail: [email protected].
Abstract: Particle swarm optimization (PSO) is a population-based intelligent algorithm for solving optimization problems. Since the fast convergence and easy implementation, PSO has been successfully applied in some areas. However, the standard PSO also has some inherent drawbacks, and the premature convergence is the main issue. Many PSO variants have been developed to solve this problem. Unlike the previous studies, this paper focuses on the communications among different particles, based on the graph theory and information theory, a new analytical method for PSO topology was proposed. By analysing three typical topologies (star, ring, and von-Neumann), the influence of different topologies was revealed. Therefore, an improved topology combines the advantages of three typical topologies was developed, and the iterations of PSO were divided into three stages. The different stages have different topologies. The benchmark test results show that the improved topology is effective. It applies to both convex and nonconvex optimizations.
Keywords: Particle swarm optimization, neighborhood topology, graph theory, information theory, dynamic topology
DOI: 10.3233/JCM-190003
Journal: Journal of Computational Methods in Sciences and Engineering, vol. 19, no. 4, pp. 955-968, 2019
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
[email protected]
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office [email protected]
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
如果您在出版方面需要帮助或有任何建, 件至: [email protected]