Conference contribution
(Conference Contribution)


Strategies for finding good local guides in multi-objective particle swarm optimization (MOPSO)


Publication Details
Author(s): Mostaghim S, Teich J
Publisher: Institute of Electrical and Electronics Engineers Inc.
Publication year: 2013
Pages range: 26-33
ISBN: 9780780379145
Event: 2003 IEEE Swarm Intelligence Symposium, SIS 2003

Abstract

In multi-objective particle swarm optimization (MOPSO) methods, selecting the best local guide (the global best particle) for each particle of the population from a set of Pareto-optimal solutions has a great impact on the convergence and diversity of solutions, especially when optimizing problems with high number of objectives. This paper introduces the Sigma method as a new method for finding best local guides for each particle of the population. The Sigma method is implemented and is compared with another method, which uses the strategy of an existing MOPSO method for finding the local guides. These methods are examined for different test functions and the results are compared with the results of a multi-objective evolutionary algorithm (MOEA).



How to cite
APA: Mostaghim, S., & Teich, J. (2013). Strategies for finding good local guides in multi-objective particle swarm optimization (MOPSO). (pp. 26-33). Institute of Electrical and Electronics Engineers Inc..

MLA: Mostaghim, Sanaz, and Jürgen Teich. "Strategies for finding good local guides in multi-objective particle swarm optimization (MOPSO)." Proceedings of the 2003 IEEE Swarm Intelligence Symposium, SIS 2003 Institute of Electrical and Electronics Engineers Inc., 2013. 26-33.

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