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Symmetry 2017, 9(1), 15; https://doi.org/10.3390/sym9010015

An Orthogonal Multi-Swarm Cooperative PSO Algorithm with a Particle Trajectory Knowledge Base

College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
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Academic Editor: Vladimir Shpilrain
Received: 18 November 2016 / Revised: 30 December 2016 / Accepted: 13 January 2017 / Published: 20 January 2017
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Abstract

A novel orthogonal multi-swarm cooperative particle swarm optimization (PSO) algorithm with a particle trajectory knowledge base is presented in this paper. Different from the traditional PSO algorithms and other variants of PSO, the proposed orthogonal multi-swarm cooperative PSO algorithm not only introduces an orthogonal initialization mechanism and a particle trajectory knowledge base for multi-dimensional optimization problems, but also conceives a new adaptive cooperation mechanism to accomplish the information interaction among swarms and particles. Experiments are conducted on a set of benchmark functions, and the results show its better performance compared with traditional PSO algorithm in aspects of convergence, computational efficiency and avoiding premature convergence. View Full-Text
Keywords: orthogonal initialization mechanism; multi-swarm PSO algorithm; adaptive cooperation mechanism orthogonal initialization mechanism; multi-swarm PSO algorithm; adaptive cooperation mechanism
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Yang, J.; Zhu, H.; Wang, Y. An Orthogonal Multi-Swarm Cooperative PSO Algorithm with a Particle Trajectory Knowledge Base. Symmetry 2017, 9, 15.

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