Multi-Objective Particles Swarm Optimization Approaches

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Author(s): Konstantinos E. Parsopoulos (University of Patras, Greece)and Michael N. Vrahatis (University of Patras, Greece)
Copyright: 2008
Pages: 23
Source title: Multi-Objective Optimization in Computational Intelligence: Theory and Practice
Source Author(s)/Editor(s): Lam Thu Bui (University of New South Wales, Australia)and Sameer Alam (University of New South Wales, Australia)
DOI: 10.4018/978-1-59904-498-9.ch002

Keywords: Artificial Intelligence / Computational Intelligence / Computer Science & IT / Engineering Science Reference

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Abstract

The multiple criteria nature of most real world problems has boosted research on multi-objective algorithms that can tackle such problems effectively, with the smallest possible computational burden. Particle Swarm Optimization has attracted the interest of researchers due to its simplicity, effectiveness and efficiency in solving numerous single-objective optimization problems. Up-to-date, there are a significant number of multi-objective Particle Swarm Optimization approaches and applications reported in the literature. This chapter aims at providing a review and discussion of the most established results on this field, as well as exposing the most active research topics that can give initiative for future research.

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