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CONTAINERIZATION METHOD FOR LOGISTIC COST REDUCTION BASED ON CLOSED-LOOP SUPPLY CHAIN MODEL

机译:基于闭环供应链模型的物流成本降低方法

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Logistics cost is an important contributor to the overall cost in a supply chain system. By using collapsible containers, the frequency of return freight can be reduced and the return of containers can be optimized, leading to potential logistic cost savings. However, the dynamic behavior of container flows due to demand, inventory, storage, and repair requirements make it difficult to accurately analyze container system performance. An accurate estimation of this collapsible container usage impact is of great importance for decision-making. This paper describes the development of a mathematical model of the container dynamic flow system by using the collapsible containers. A continuous time, discrete space Markov process is used for stochastic scenario. The model determines the total cost savings, based on the collapsible rate, the number of collapsible containers, the performance of the factory and the supplier and the transportation environment. The presented mathematical formulation enables the evaluation of the system performance. A case study of collapsible container supply chain system demonstrates the advantages of this methodology. In addition, a simulation model of this stochastic system is presented to verify the mathematical model. Simulation tests are conducted to demonstrate the potential logistics cost savings in the closed-loop supply chain system.
机译:物流成本是供应链系统中总体成本的重要因素。通过使用可折叠集装箱,可以减少返程货运的频率,并可以优化集装箱的返程,从而节省了物流成本。但是,由于需求,库存,存储和维修要求而引起的集装箱流的动态行为,使得很难准确地分析集装箱系统的性能。准确估计这种可折叠容器使用的影响对于决策至关重要。本文介绍了使用可折叠容器开发容器动态流系统数学模型的过程。连续时间,离散空间马尔可夫过程用于随机情景。该模型基于可折叠率,可折叠容器的数量,工厂和供应商的绩效以及运输环境来确定总的成本节省。提出的数学公式使您能够评估系统性能。以可折叠集装箱供应链系统为例的研究证明了这种方法的优势。另外,给出了该随机系统的仿真模型以验证数学模型。进行模拟测试以证明在闭环供应链系统中潜在的物流成本节省。

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