Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/864
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Title: A particle swarm optimization-based method for multiobjective design optimizations
Authors: Ho, SL 
Yang, S
Ni, G
Lo, E 
Wong, HCC
Issue Date: May-2005
Source: IEEE transactions on magnetics, May 2005, v. 41, no. 5, p. 1756-1759
Abstract: A particle swarm optimization (PSO) based algorithm for finding the Pareto solutions of multiobjective design problems is proposed. To enhance the global searching ability of the available PSOs, a novel formula for updating the particles' velocity and position, as well as the introduction of craziness, are reported. To handle a multiobjective design problem using the improved PSO, a new fitness assignment mechanism is proposed. Moreover, two repositories, together with the age variables for their members, are introduced for storing and selecting the previous best positions of the particle as well as that of its companions. Besides, the use of age variables to enhance the diversity of the solutions is also described. The proposed method is tested on two numerical examples with promising results.
Keywords: Inverse problem
Multiobjective optimal algorithm
Optimal design
Particle swarm optimization (PSO)
Publisher: Institute of Electrical and Electronics Engineers
Journal: IEEE transactions on magnetics 
ISSN: 0018-9464
EISSN: 1941-0069
DOI: 10.1109/TMAG.2005.846033
Rights: © 2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
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