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

Mostaghim S, Teich J (2004)


Publication Status: Published

Publication Type: Conference contribution, Conference Contribution

Publication year: 2004

Book Volume: 2

Pages Range: 1404-1411

Conference Proceedings Title: Proceedings of the Congress on Evolutionary Computation (CEC '04)

Event location: Portland, OR US

ISBN: 9780780385153

URI: https://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=4344649636&origin=inward

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.

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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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