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
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.
Authors with CRIS profile
Related research project(s)
Involved external institutions
Germany (DE)How to cite
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.
BibTeX: Download