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Packed parts delivery problem of automotive inbound logistics with a supplier park

机译:带有供应商园区的汽车入库物流的包装件交付问题

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This paper considers a truck scheduling problem of delivering different types of parts from a supplier park to an automotive assembly plant. A supplier park is a cluster of suppliers located adjacent to an assembly plant. The parts of each type are picked up from the corresponding supplier in the park and are delivered to a buffer beside a given station of the assembly line in predetermined homogeneous packages. On a finite time horizon, the initial inventory level of each buffer at the beginning of the horizon and the quantity of each type of parts consumed on each point are given. Our problem is to make delivery schedules for capacitated trucks such that the total transportation time is minimized, and the inventory level of each buffer is within a given range at any moment within the horizon. A time-indexed integer linear programming (IP) model is proposed for the problem, and a column generation based algorithm (CGBB) is developed to solve the problem efficiently. Computational experiments based on randomly generated data and a case study based on real data collected from one of the major automotive manufacturers in China are conducted, respectively. The results show that the proposed CGBB algorithm outperforms solving the IP model by CPLEX and the greedy method used in practice. It is capable of generating high quality solutions for the problem efficiently, and is practical to be used in daily operations. (C) 2018 Elsevier Ltd. All rights reserved.
机译:本文考虑了从供应商园区向汽车装配厂交付不同类型零件的卡车调度问题。供应商园区是位于组装工厂附近的一组供应商。每种类型的零件都是从园区中的相应供应商处拾取的,并以预定的均匀包装形式输送到装配线给定工位旁边的缓冲器中。在有限的时间范围内,给出了范围开始时每个缓冲区的初始库存水平以及在每个点上消耗的每种零件的数量。我们的问题是制定有能力的卡车的交货时间表,以使总运输时间最小化,并且每个缓冲区的库存水平在地平线范围内的任何时刻都处于给定范围内。针对该问题提出了时间索引整数线性规划(IP)模型,并开发了基于列生成的算法(CGBB)以有效解决该问题。分别进行了基于随机生成数据的计算实验和基于从中国主要汽车制造商之一收集的真实数据的案例研究。结果表明,所提出的CGBB算法优于通过CPLEX和贪婪方法求解IP模型。它能够有效地为该问题生成高质量的解决方案,并且非常实用,可用于日常操作。 (C)2018 Elsevier Ltd.保留所有权利。

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