Multi Objective Particle Swarm Optimization: A Survey

In this current scenario, choosing any one choice among multiple conflicting objective is became the common problem. These problems are considered to be solved through the decision being made for the given objective is best compromising solution i.e. the solution satisfying all the objectives. Particle swarm optimization is one of meta-heuristic mechanism being used to find solution from the solution space. It belongs to evolutionary algorithm as it is population based optimization technique which figured out to be efficient, effective, flexible and easy implementation. Changes have been made in original particle swarm optimization techniques result in better solutions for multi objective optimization problems. This paper provides the basic known concepts of multi objective optimization as well as of particle swarm optimization. This results in better understanding of the concept of multi objective particle swarm optimization. Here, we also discussed the concepts of multi objective particle swarm optimization, techniques used in multi objective particle swarm optimization, approaches applied in multi objective particle swarm optimization and some of the future related work directions are also being included. Keywords—Multi objective particle swarm optimization(MOPSO); Multi objective optimization problems(MOOPs); Particle swarm optimization(PSO); Pareto optimality; Pareto front.

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