物流运输快速配送路径规划仿真

发布时间：2018-04-29 22:09

本文选题：物流运输 + 快速配送　；参考：《计算机仿真》2017年08期

【摘要】：对物流运输快速配送路径进行规划,能够有效提高物流配送效率。对物流运输快速配送路径的规划,需要先确定路径权值,给出物流运输路径规划目标函数,完成物流配送路径规划。传统方法采用遗传算法优化运输路径,通过调整运输路径满足约束条件,但忽略了路径规划目标函数的计算。提出基于蚁群算法的数据包络分析下物流运输快速配送路径规划方法。考虑物流运输快速配送路网约束组建物流运输快速配送路径规划数学模型,第一阶段以均衡货物运输车辆任务负载为目标进行车辆配送区域划分,第二阶段以最小化运输车辆工作量和配送行程时耗为目标,给出物流运输快速配送路径规划综合测度函数,采用模糊数学的权值确定理论确定物流运输快速配送路径权值,给出物流运输快速配送路径规划目标函数,对运输路径实现优化选择。实验结果表明,所提方法在路径规划效率与收敛速度上有明显提高。
[Abstract]:Planning the fast distribution route of logistics transportation can effectively improve the efficiency of logistics distribution. To plan the fast distribution path of logistics transportation, it is necessary to determine the value of the path weight, give the objective function of the route planning of logistics transportation, and complete the path planning of logistics distribution. The traditional genetic algorithm is used to optimize the transportation path, and the transportation path is adjusted to meet the constraints, but the calculation of the path planning objective function is ignored. Based on ant colony algorithm (ACA), a data envelopment analysis method for fast distribution path planning of logistics transportation is proposed. Considering the constraints of logistics transportation rapid distribution network, a mathematical model of logistics transportation rapid distribution path planning is established. In the first stage, the vehicle distribution area is divided with the goal of balancing the load of cargo transport vehicles. In the second stage, aiming at minimizing the workload of transportation vehicles and the consumption of distribution travel time, the comprehensive measure function of logistics transportation rapid distribution path planning is given, and the weight determination theory of fuzzy mathematics is used to determine the weight value of logistics transportation rapid distribution path. The objective function of route planning for fast distribution of logistics transportation is given, and the optimal selection of transportation route is realized. The experimental results show that the proposed method can improve the efficiency and convergence speed of path planning.
【作者单位】：江西农业大学南昌商学院;
【基金】：江西省教育厅科学技术研究项目(GJJ161549)
【分类号】：O221

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