基于改进交叉熵算法的同城物流交叉转运路径分组规划

Grouping Planning of Cross Transfer Paths in Intra City Logistics Based on Improved Cross Entropy Algorithm

为了达到最优的同城物流配送路径和组合方式,针对当前算法中目标函数与约束条件冗余,最短配送距离容易陷入局部最优解的问题,设计基于改进交叉熵算法的同城物流交叉转运路径分组规划方法。构建道路拥堵状态函数,实时监测和更新状态函数,描述道路网络中各个路径的拥堵程度。以最短配送距离为目标,引入交叉熵算法,考虑转运路径变换问题,根据当前精英解集中的最优解调整概率密度函数参数,应用粒子群算法改进交叉熵算法,获取与实时更新最优配送路径。实验结果表明,所提方法的同城物流交叉转运路径分组规划转运次数少,出发次数、转弯次数和路径总长度值均较低,整体应用效果较好。

In order to achieve the optimal intra city logistics distribution path and combination method,and to address the problem of redundant objective functions and constraint conditions,as well as the tendency of the shortest delivery distance to fall into local optima solution,an intra city logistics cross transfer path grouping planning method based on an improved cross entropy algorithm is designed.This paper constructs a road congestion state function,monitors and updates the state function in real time,describes the congestion degree of each path in the road network,with the shortest delivery distance as the goal,introduces the cross entropy algorithm,considers the problem of transfer path transformation,adjusts the probability density function parameters based on the optimal solution in the current elite solution set,applies particle swarm optimization algorithm to improve the cross entropy algorithm,obtains and updates the optimal delivery path in real time.The experimental results show that the proposed method has fewer transfer times,lower departure times,turning times,and total path length values for cross transportation path planning in the same city logistics.The overall application effect is better.