Multi-Objective Particle Swarm Optimizers: A Survey of the State-of-the-Art

摘要: The success of the Particle Swarm Optimiza- tion (PSO) algorithm as a single-objective optimizer (mainly when dealing with continuous search spaces) has motivated re- searchers to extend use this bio-inspired technique other areas. One them is multi-objective optimization. De- spite fact that first proposal Multi-Objective Par- ticle Optimizer (MOPSO) over six years old, con- siderable number algorithms have been proposed since then. This paper presents comprehensive review vari- ous MOPSOs reported in specialized literature. As part review, we include classification approaches, and identify main features each proposal. In last paper, list some topics within field consider promising areas future research.