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Vector coevolving particle swarm optimization algorithm
School of Computer Science and technology, Engineering Research Center of Digital Media Technology, Ministry of Education, Shandong University, Jinan.
School of Computer Science and technology, Engineering Research Center of Digital Media Technology, Ministry of Education, Shandong University, Jinan.
School of Computer Science and technology, Engineering Research Center of Digital Media Technology, Ministry of Education, Shandong University, Jinan.
Shandong Provincial Key Laboratory of Network based Intelligent Computing, University of Jinan.
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Number of Authors: 5
2017 (English)In: Information Sciences, ISSN 0020-0255, E-ISSN 1872-6291, Vol. 394-395, 273-298 p.Article in journal (Refereed) Published
Abstract [en]

In this paper, we propose a novel vector coevolving particle swarm optimization algorithm (VCPSO). In VCPSO, the full dimension of each particle is first randomly partitioned into several sub-dimensions. Then, we randomly assign either one of our newly designed scalar operators or learning operators to update the values in each sub-dimension. The scalar operators are designed to enhance the population diversity and avoid premature convergence. In addition, the learning operators are designed to enhance the global and local search ability. The proposed algorithm is compared with several other classical swarm optimizers on thirty-three benchmark functions. Comprehensive experimental results show that VCPSO displays a better or comparable performance compared to the other algorithms in terms of solution accuracy and statistical results.

Place, publisher, year, edition, pages
2017. Vol. 394-395, 273-298 p.
National Category
Media and Communication Technology
Research subject
Mobile and Pervasive Computing
Identifiers
URN: urn:nbn:se:ltu:diva-61834DOI: 10.1016/j.ins.2017.01.038ISI: 000396973000016Scopus ID: 2-s2.0-85012262497OAI: oai:DiVA.org:ltu-61834DiVA: diva2:1071719
Note

Validerad; 2017; Nivå 2; 2017-03-21 (rokbeg)

Available from: 2017-02-06 Created: 2017-02-06 Last updated: 2017-04-20Bibliographically approved

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CiteExportLink to record
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