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Multi-task transportation scheduling model with backhauls based on hub and spoke in collaborative logistics network

机译:协同物流网络中基于中心和轮辐的带回程的多任务运输调度模型

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摘要

Hub and spoke collaborative logistics network has recently received considerable attention in terms of resource scheduling problem. In view of that problem such as low scale merit, inefficient resource utilization and conflict of interest between the operator and customer in the process of network operation, the paper seeks to formulate the scheduling strategy for multiple logistics tasks oriented to multi-origin and multi-destination on the basis of multiple-allocation-hybrid H&S collaborative network (including two layers). Taking the backhaul resource, resource departure time, capability limitation, task delay penalty, etc. into account, the aim of the problem is to minimize both total cost and total time for the task set. According to the characteristics of the problem, the immune genetic algorithm based on three-layer encoding mechanism is designed to solve the model. Moreover, the models and algorithms are validated by extensive results of numerical examples.
机译:在资源调度问题方面,轮辐式协同物流网络最近受到了相当大的关注。针对网络运营过程中规模小,资源利用效率低以及运营商与客户之间的利益冲突等问题,本文寻求制定针对多源,多源的多种物流任务的调度策略。 H&S多重协作混合网络(包括两层)的基础上建立目的地。考虑到回程资源,资源离开时间,能力限制,任务延迟损失等,问题的目的是使任务集的总成本和总时间最小化。根据问题的特点,设计了基于三层编码机制的免疫遗传算法对模型进行求解。此外,通过大量的数值例子验证了模型和算法的有效性。

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