An inventory optimization model based on BP neutral network

Weipeng Wang
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引用次数: 2

Abstract

In traditional enterprise management mode, there is no necessary information for the inventory optimization, it is very difficult to get the optimal solution meeting the actual requirements in the process of solving the model. On the base of analyzing the problems of the traditional inventory optimization model, this study shows that inventory optimization should be directed by the thought of supply chain management, the neural network model as a tool, using the BP neural networks to integrate a variety of effective information, improving the traditional inventory optimization model, and then a more satisfactory inventory optimization strategy. And based on the actual inventory circumstances of a company, we give the specific application case.
基于BP神经网络的库存优化模型
在传统的企业管理模式中,库存优化没有必要的信息,在求解模型的过程中很难得到满足实际需求的最优解。在分析传统库存优化模型存在问题的基础上,提出库存优化应以供应链管理的思想为指导,以神经网络模型为工具,利用BP神经网络整合各种有效信息,对传统的库存优化模型进行改进,进而提出更令人满意的库存优化策略。并结合某公司的实际库存情况,给出了具体的应用案例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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