物流配送路线优化粒子群改进算法  

Improved Algorithm of Particle Swarm Optimization for Logistics Distribution Route

作　　者：陈艳[1] CHEN Yan(School of Mechanical and Electrical Engineering,Chizhou University,Chizhou 247000,China)

机构地区：[1]池州学院机电工程学院,安徽池州247000

出　　处：《浙江水利水电学院学报》2019年第2期69-74,共6页Journal of Zhejiang University of Water Resources and Electric Power

摘　　要：物流运输中心配送路线优化是关系到物流企业核心竞争力的一个关键且复杂的优化问题,难以精确求解。为节省物流成本,提出了一种粒子群改进算法并将其应用于物流中心配送路线优化问题,即在惯性权重线性递减的基础上,加入了混沌随机数扰动,使惯性权重有概率的适度增加,以便进行全局搜索,从而防止局部收敛;并针对采用固定加速度系数容易使得粒子群算法陷入局部极值的缺点,提出了一种随机加速度系数的方法,具体实际算例的仿真结果表明,改进算法的优化性能更佳。Distribution route optimization of logistics center is a key and complex scheduling problem relevant to core competence of logistics enterprises, and is also difficult to solve. In order to save the logistics cost, an improved particle swarm optimization (PSO) algorithm is proposed in distribution route optimization of logistics center. Based on the linear decreasing inertia weight, the chaotic constant disturbance is added to increase the inertia weight with little probability, so as to get rid of the local search and get the global search. Meanwhile, a method about random acceleration coefficients is proposed in order to solve the fault that two algorithms easily fall into partial extremal. The simulation results of specific practical example show that the improved algorithm has more powerful optimization capability.

关 键 词：配送路线优化 粒子群 惯性权重递减 混沌随机数扰动 随机加速度系数 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]