Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/859
Title: Incorporating a priori preferences in a vector PSO algorithm to find arbitrary fractions of the pareto front of multiobjective design problems
Authors: Ho, Siu-lau
Yang, Shiyou
Ni, Guangzheng
Subjects: Desirability function
Multiobjective design
Particle swarm optimization (PSO) algorithm
Reference point
Algorithms
Decision making
Multiobjective optimization
Pareto principle
Problem solving
Issue Date: Jun-2008
Publisher: IEEE
Source: IEEE transactions on magnetics, June 2008, v. 44, no. 6, p. 1038-1041
Abstract: To incorporate the knowledge or preference of a decision maker or domain expert into a vector optimizer in the search for a series of subsets of the entire Pareto optimal solutions, a vector particle swarm optimization (PSO) algorithm that implements the reference point-based approach together with a desirability function is proposed. The fitness assignment strategy and the neighborhood relationship of the PSO algorithm are redefined to facilitate the realization of the aforementioned objective. To validate and demonstrate the advantages of the proposed algorithm, its applications on two different multiobjective problems are reported.
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Type: Journal/Magazine Article
URI: http://hdl.handle.net/10397/859
DOI: 10.1109/TMAG.2007.914861
ISSN: 0018-9464
Appears in Collections:EE Journal/Magazine Articles

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