A Novel Boundary Based Multiobjective Particle Swarm Optimization

摘要

A novel boundary based multiobjective particle swarm optimization is presented in this paper. The proposed multiobjective optimization algorithm searches the border of the objective space unlike other current proposals to look for the Pareto solution set to solve such problems. In addition, we apply the proposed method to other particle swarm optimization variants, which indicates the strategy is highly applicatory. The proposed approach is validated using several classic test functions, and the experiment results show efficiency in the convergence performance and the distribution of the Pareto optimal solutions.