多枢纽轴辐式协同物流网络任务-路径优化匹配研究

针对物流网络运营中规模效益低、运营商与客户利益冲突等问题，本文提出了基于多枢纽轴辐式协同物流网络的任务-路径优化匹配策略。在网络结构确定的条件下，从物流集成服务商角度出发，综合考虑资源发车时刻、路径能力限制、动态成本折扣系数以及任务延时惩罚，构建了以总物流成本最小和时间最短为优化目标的轴辐式协同物流网络任务-路径优化匹配数学模型。根据问题特点，设计了基于三层编码的遗传算法对模型进行求解，同时配合多点交叉、变异机制提高求解效率。研究结果表明，集并运输能够大幅度降低任务集执行成本，但当集并带来的交货延迟、客户满意度降低等负面效应超过其正面效应时，需适当匹配直达线路以提高整体效益。

Optimization of Task-Route Matching Based on Muti-Hub and Spoke Collaborative Logistics Network

To advance scale merit of the logistics network, and balance the conflicts of interests between operators and customers, an optimization strategy of task-route matching is proposed on the basis of multi-hub and spoke collaborative logistics network.Firstly, under the condition of a given logistics network, considering resource departure time, capability limitation, dynamic cost discount coefficient and task delay penalty, a mathematical model oftask-route matching is established, which is from the point of logistics integration service provider and committed tominimize total cost as well as total time. Then,according to the characteristics of the problem, the genetic algorithm based on three-layers code is designed to solve the model. Meanwhile,the multi-point crossover and mutation mechanism are used to improve computing efficiency.Finally, research results show that centralized transportation could significantly reduce the execution cost of the task set,however, when the negative effect such as delivery delay and customer satisfaction decrease have exceeded the positive effect it brought about, the direct transport route should be appropriately introduced to improve the overall benefit.