International Journal of Computational
Intelligence Research (IJCIR)
Volume 2, Number 3 (2006)
Multi-Objective particle swarm optimizers: A survey of the state-of-the-art
Margarita Reyes-Sierra, Carlos A. Coello Coello
CINVESTAV-IPN (Evolutionary Computation Group), Electrical Engineering Department, Computer Science Section, Av. IPN No. 2508, Col. San Pedro Zacatenco, Méexico
D.F. 07300, MÉXICO
The success of the Particle Swarm Optimization (PSO) algorithm as a single-objective optimizer (mainly when dealing with continuous search spaces) has motivated researchers to extend the use of this bio-inspired technique to other areas. One of them is multi-objective optimization. Despite the fact that the first proposal of a Multi-Objective Particle Swarm Optimizer (MOPSO) is over six years old, a considerable number of other algorithms have been proposed since then. This paper presents a comprehensive review of the various MOPSOs reported in the specialized literature. As part of this review, we include a classification of the approaches, and we identify the main features of each proposal. In the last part of the paper, we list some of the topics within this field that we consider as promising areas of future research.