关键词: 内分泌系统, 非劣解, 类全局最优, 粒子群优化算法

Abstract: A novel multi-object Particle Swarm Optimization algorithm（PSO） based on supervising and controlling principles of endocrine system is proposed.According to the modulation principle of controlling method between stimulation hormones and releasing hormones，considering the supervision and controlling of individual in the set of non-dominated for the nearest class of swarm，the global optimization position of class is introduced in the position updating process of particles.The new position of particles is not only determined by the best position which it achieves so far and the global best position in current generation，but also influenced by the best position of class，so the global information and local information is combined completely.The new method of updating for particle swarm is designed.In order to validate the effectiveness of given method three benchmark multi-objective problems are simulated by the given method，MOPSO and NSGA-II，the results indicate that the given method has better performance in convergence and distribution than MOPSO and NSGA-II.

Key words: endocrine system, non-dominated solution, global optimization of the class, Particle Swarm Optimization algorithm（PSO）