Dynamic Particle Swarm Optimization to Solve Multi-objective Optimization Problem

Multi-objective optimization problem is reaching better understanding of the properties and techniques of evolutionary algorithms. This paper presents the Dynamic Particle Swarm Optimization algorithm for solving multiobjective optimization problem. This Dynamic PSO is different from the existing PSO's and some local version of PSO in terms of swarm size, topology and search space. In this paper swarm size criteria for dynamic PSO is considered. Experiment conducted for standard benchmark functions of multi-objective optimization problem, which shows the better performance rather the basic PSO.