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|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|
|Subjects: ||Desirability function|
Particle swarm optimization (PSO) algorithm
|Issue Date: ||Jun-2008 |
|Citation: ||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.|
|Rights: ||© 2008 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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|Type: ||Journal/Magazine Article|
|Appears in Collections:||EE Journal/Magazine Articles|
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