Soniya Lalwani - Statistician, R & D, Advanced Bioinformatics Centre, Birla Institute of Scientific Research, Jaipur PhD student, Department of Mathematics, Malaviya National Institute of Technology, Jaipur
Sorabh Singhal - Project student, R & D, Advanced Bioinformatics Centre, Birla Institute of Scientific Research, Jaipur
Rajesh Kumar - Associate Professor, Department of Electrical Engineering, Malaviya National Institute of Technology, Jaipur
Nilama Gupta - Associate Professor, Department of Mathematics, Malaviya National Institute of Technology, Jaipur

Numerous problems encountered in real life cannot be actually formulated as a single objective problem; hence the requirement of Multi-Objective Optimization (MOO) had arisen several years ago. Due to the complexities in such type of problems powerful heuristic techniques were needed, which has been strongly satisfied by Swarm Intelligence (SI) techniques. Particle Swarm Optimization (PSO) has been established in ۱۹۹۵ and became a very mature and most popular domain in SI. Multi-Objective PSO (MOPSO) established in ۱۹۹۹, has become an emerging field for solving MOOs with a large number of extensive literature, software, variants, codes and applications. This paper reviews all the applications of MOPSO in miscellaneous areas followed by the study on MOPSO variants in our next publication. An introduction to the key concepts in MOO is followed by the main body of review containing survey of existing work, organized by application area along with their multiple objectives, variants and further categorized variants.

Multi-Objective Particle Swarm Optimization, Conflicting objectives, Particle Swarm Optimization, Pareto Optimal Set, Non-dominated solutions