Covering Pareto-optimal fronts by subswarms in multi-objective particle swarm optimization

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Details zur Publikation

Autorinnen und Autoren: Mostaghim S, Teich J
Jahr der Veröffentlichung: 2004
Band: 2
Tagungsband: Proceedings of the Congress on Evolutionary Computation (CEC '04)
Seitenbereich: 1404-1411
ISBN: 9780780385153


Abstract


Covering the whole set of Pareto-optimal solutions is a desired task of multi-objective optimization methods. Because in general it is not possible to determine this set, a restricted amount of solutions are typically delivered in the output to decision makers. In this paper, we propose a new method using multi-objective particle swarm optimization to cover the Pareto-optimal front. The method works in two phases. In phase 1 the goal is to obtain a good approximation of the Pareto-front. In a second run subswarms are generated to cover the Pareto-front. The method is evaluated using different test functions and compared with an existing covering method using a real world example in antenna design.



FAU-Autorinnen und Autoren / FAU-Herausgeberinnen und Herausgeber

Teich, Jürgen Prof. Dr.-Ing.
Lehrstuhl für Informatik 12 (Hardware-Software-Co-Design)


Einrichtungen weiterer Autorinnen und Autoren

Universität Paderborn


Zitierweisen

APA:
Mostaghim, S., & Teich, J. (2004). Covering Pareto-optimal fronts by subswarms in multi-objective particle swarm optimization. In Proceedings of the Congress on Evolutionary Computation (CEC '04) (pp. 1404-1411). Portland, OR, US.

MLA:
Mostaghim, Sanaz, and Jürgen Teich. "Covering Pareto-optimal fronts by subswarms in multi-objective particle swarm optimization." Proceedings of the Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004, Portland, OR 2004. 1404-1411.

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Zuletzt aktualisiert 2018-08-08 um 15:53