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 the use of this bio-inspired technique to other areas. One of them is multi-objective optimization. De- spite the fact that the first proposal of a Multi-Objective Par- ticle Swarm Optimizer (MOPSO) is over six years old, a con- siderable number of other algorithms have been proposed since then. This paper presents a comprehensive review of the vari- ous 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.