关于物流系统车辆配送路径规划仿真

The Simulation of Logistics Vehicle Routing Planning

在物流系统车辆配送路径的研究中,针对当前物流系统配送车辆路径规划涉及影响因素多、配送成本高、算法复杂度高的问题,为加强物流系统车辆配送效率,对路径规划进行科学决策,采用粒子群算法解决物流配送车辆路径规划问题。由于粒子群算法存在局部收敛与早熟的不足,将加速因子与惯性权重相关联,提出了一种改进的粒子群算法。最后结合实例对改进的粒子群算法在车辆配送路径规划问题中的应用进行仿真。结果表明,改进后的粒子群算法在避免前期局部收敛、提高后期收敛精度和速度方面具有良好的效果,为解决物流系统车辆配送路径规划问题提供了科学的手段和途径。

This paper researched the vehicle routing problem（ VRP） and optimized the particle swarm optimization（ PSO）. Considering many influencing factors,such as high distribution costs,and high complexity algorithm on the VRP,in order to provide scientific decision-making to the logistic vehicle routing planning,the model of vehicle routing problem was optimized and the PSO algorithm was used to solve the problem. To avoid the local convergence and immature of PSO algorithm,this paper proposed an improved PSO（ IPSO） algorithm which improved accelerating factor and random number,and combined accelerating factor and inertia weight. The simulation experiments show that our method on one hand,performs well on preventing local convergence at the earlier stage,and on the other hand,improves convergence accuracy and speed in the later period. The improved PSO provides an effective way to solve the vehicle routing problem