Multiobjective optimization using dynamic neighborhood particle swarm optimization

著者: Xiaohui Hu, Russell C. Eberhart - Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600) 2002 被引用: 611

This paper presents a particle swarm optimization (PSO) algorithm for multiobjective optimization problems. PSO is modified by using a dynamic neighborhood strategy, new particle memory updating, and one-dimension optimization to deal with multiple objectives. Several benchmark cases were tested and showed that PSO could efficiently find multiple Pareto optimal solutions.