综合密度信息的矢量变异多目标粒子群优化

摘要

For particle swarm optimization, when it is applied to multi-objective problems there may exist some problems concerning convergence, especially during the later part of iterations.Meanwhile the distribution of solutions needs to be en-hanced.A novel multiple-objective particle swarm optimization algorithm is designed in order to solve the above problems.An integrated strategy of finding global best for particle in swarm is presented based on sigma method and solution density in-formation.The proposed algorithm mutates the particles' velocities by vector disturbance and helps the stagnated particles escape from local optima.The results show that-the proposed algorithm has great advantages in convergence,distribution and diversity of solutions than classical algorithms.%粒子群优化算法求解多目标优化问题存在早熟收敛和后期收敛速性差的不足,解的分布性也有待提高.为此设计一种新的多目标粒子群优化算法:对寻求粒子最优解的sigma方法进行改进,提出一种综合非支配解密度信息和sigma值的最优解求解机制.对变异粒子速度进行矢量扰动变异；对停滞粒子进行位置变异,有效避免算法的早熟收敛问题.测试结果表明,所提出的算法在收敛性和解的分布性、多样性方面较经典的算法具有明显的优势.