Multi-Objective Particle Swarm Optimization (MOPSO)

Particle Swarm Optimization (PSO) is one of the Evolutionary Algorithm (EA) that was develop and proposed by Kennedy and Eberhart based on the inspiration from flock of birds which the main aim is to find food. This algorithm implementation has solved a wide variety of single-objective optimization and has proven to produce a very good result with a low computational cost. Therefore, Moore and Chapman proposed the first extension of the PSO strategy called Multi-Objective Particle Swarm Optimization (MOPSO) algorithm to solve the multi-objective problems. As of now, there are more than 30 diverse variation of MOPSO that has been reported and most of the studies focuses on the leader selection, elitism, algorithmic convergence and diversity.