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: Zhou, Xiaofeng | Miao, Xiaoping*
Affiliations: College of Defense Engineering, PLA University of Science and Technology, Nanjing, China
Correspondence: [*] Corresponding author. Xiaoping Miao, College of Defense Engineering, PLA University of Science and Technology, Nanjing, China. Tel.: +86 02580825333; mxp5757@163.com
Abstract: What kind of information is used and in which way the particles interact with each other have direct effects on the particle swarm optimization (PSO) algorithm efficiency. In order to use the information more fully, effectively and reasonably, the paper proposes a fully and discriminatorily informed PSO (FDIPSO) algorithm. Unlike the traditional PSO algorithm, the algorithm takes the positive effects of all the superior neighbors and the negative effects of the inferior particles into account and employs different mechanisms for attractive and repulsive effects to prevent confusion of swarm evolution caused by the different effects. The superior information is fully used to build high quality equilibrium points as attractors to guide particles while the repulsive effect from inferior information is embodied by introducing an ‘escape coefficient’ to help adjust the movement of particles. Experimental studies are conducted on a set of well-known benchmark functions including unimodal, multimodal and rotated problems. Computational results show positive effect and negative effect work collaboratively in FIDPSO, verify the relative superiority of this strategy over four other information sharing strategies and indicate that the approach outperforms several other state-of-art PSO variants on the test problems.
Keywords: Particle swarm optimization, swarm intelligence, information sharing strategy, escape coefficient
DOI: 10.3233/IFS-151587
Journal: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 1, pp. 195-207, 2015
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
sales@iospress.com
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
info@iospress.nl
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office info@iospress.nl
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
china@iospress.cn
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
如果您在出版方面需要帮助或有任何建, 件至: editorial@iospress.nl