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The Study of VMI Inventory Decision Support System using Neural Network Technology

机译:基于神经网络技术的VMI库存决策支持系统研究

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Supply chain management includes four major elements; namely, manufacturers, suppliers, distributors and retailers. Inventory control plays a very important role in each of the four modules in the supply chain. In this paper, a decision surface modeling tool is developed using neural networks. It is capable of capturing the essential features of the retail simulation model in multidimensional, mathematical relationships between performance (e.g., service level and lost sales) and key decision parameters (e.g., SKU mix and season length). The simulation model is used to generate the training data. Once trained, the neural network is able to predict performance for new sets of inputs in real-time and can be used to build an interactive, graphical representation of the input-performance relationships.
机译:供应链管理包括四个主要元素;即制造商,供应商,分销商和零售商。库存控制在供应链中的四个模块中的每一个中起着非常重要的作用。本文使用神经网络开发了决策表面建模工具。它能够在性能(例如,服务水平和销售丢失)和关键决策参数(例如,SKU MIX和季节)之间的多维,数学关系中捕获零售仿真模型的基本特征。仿真模型用于生成培训数据。一旦训练,神经网络就能实时预测新的输入集的性能,并且可用于构建输入性能关系的交互式图形表示。

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