A comprehensive survey: Applications of multi-objective particle swarm optimization (MOPSO) algorithm

Document Type: Research Paper

Authors

1 Statistician, R & D, Advanced Bioinformatics Centre, Birla Institute of Scientific Research, Jaipur PhD student, Department of Mathematics, Malaviya National Institute of Technology, Jaipur

2 Project student, R & D, Advanced Bioinformatics Centre, Birla Institute of Scientific Research, Jaipur

3 Associate Professor, Department of Electrical Engineering, Malaviya National Institute of Technology, Jaipur

4 Associate Professor, Department of Mathematics, Malaviya National Institute of Technology, Jaipur

Abstract

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 1995 and became a very mature and most popular domain in SI. Multi-Objective PSO (MOPSO) established in 1999, 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.

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Abido (2007). Multiobjective particle swarm for environmental/economic dispatch problem. International Power Engineering Conference. , 1385-1390
M. A. Abido (2010). Multiobjective particle swarm optimization for optimal power flow problem. Handbook of Swarm Intelligence, adaptation, learning and optimization, Springer. , 241-268
S. Agrawal, B. K. Panigrahi and M. J. Tiwari (2008). Multiobjective particle swarm algorithm with fuzzy clustering for electrical power dispatch. IEEE Transactions on Evolutionary Computation. 12 (5), 529-541
A. Ajami and M. Armaghan (2010). Application of multi-objective PSO algorithm for power system stability enhancement by means of SSSC. International Journal of Computer and Electrical Engineering. 2 (5), 838-845
B. Alatas and E. Akin (2009). Multi-objective rule mining using a chaotic particle swarm optimization algorithm. Knowledge Based Systems. 22 (6), 455-460