基于数据的钢铁原料采购库存优化研究

发布时间：2018-02-12 10:50

本文关键词： 原料钢铁工业采购库存数据驱动　出处：《东北大学》2014年硕士论文　论文类型：学位论文

【摘要】：钢铁工业是现代国民经济支柱性产业之一,对国民经济的稳定和发展具有极其重要的意义。作为资源消耗型工业,当前我国钢铁工业中的大多数企业存在库存过多、资金占用率高、能耗大、产能过剩等生产及管理等方面的问题。同时,由于原材料价格上涨,决定性技术革新速度减慢、市场逐渐饱和等一系列行业因素影响,钢铁企业的利润空间变小,生存压力增大。因此,将目光投向占用企业流动资金70%以上的原料端,规范企业生产流程、提高企业库区管理对提高企业竞争力,扩大利润空间尤为重要。本文对钢铁企业原料采购库存问题进行研究,旨在合理制定原料采购和库存策略,从而降低企业相关成本,保障生产的前提下尽量减少呆滞库存。本文的研究背景为需求不确定条件下的钢铁原料采购及库存优化问题,通过历史数据进行分析,建立单一的集成优化模型,并采用标准优化软件CPLEX对建立的模型进行求解。本文具体架构如下:(1)问题的提出与分析:首先对钢铁企业采购库存现状及存在的问题进行总结,并对比分析几种比较成熟的采购库存策略,了解其如何应用于钢铁原料解决采购库存优化问题。(2)历史生产数据的作用与分析:对钢铁企业生产过程中积累的历史数据进行分析,发现其内在联系及相应规律。探讨如何利用历史生产数据解决需求不确定情况下的钢铁原料采购库存优化问题,从而为企业原料采购库存计划编制提供决策依据,降低运营管理成本。(3)优化模型的建立与求解:利用历史生产数据建立钢铁企业采购库存问题优化模型,将历史数据直接引入模型作为输入参数,将数据和优化纳入统一的框架中进行整体考虑,并使用标准优化软件CPLEX对模型进行求解,从而制定基于历史数据考虑的采购库存优化决策。
[Abstract]:Iron and steel industry is one of the pillar industries of the modern national economy, which is of great significance to the stability and development of the national economy. High capital occupancy, high energy consumption, overcapacity and other production and management problems. At the same time, due to a series of industry factors, such as rising prices of raw materials, slowing down the speed of decisive technological innovation, and gradually saturation of the market, etc. The profit space of iron and steel enterprises becomes smaller, and the survival pressure is increased. Therefore, we should focus on the raw materials that occupy more than 70% of the current capital of the enterprise, standardize the production process of the enterprise, and improve the management of the reservoir area of the enterprise to enhance the competitiveness of the enterprise. It is very important to enlarge the profit space. This paper studies the stock of raw materials in iron and steel enterprises in order to make reasonable purchase of raw materials and stock strategy so as to reduce the related costs of enterprises. The research background of this paper is the iron and steel raw material purchasing and inventory optimization problem under uncertain demand condition. Through the analysis of historical data, a single integrated optimization model is established. And the standard optimization software CPLEX is used to solve the model. The specific framework of this paper is as follows: first of all, this paper summarizes the current situation and problems of iron and steel enterprise purchasing inventory. Several mature purchasing inventory strategies are compared and analyzed to find out how to apply them to iron and steel raw materials to solve the problem of stock optimization. The function and analysis of historical production data are analyzed. The historical data accumulated in the production process of iron and steel enterprises are analyzed. Find out its internal relation and corresponding law, discuss how to use historical production data to solve the problem of steel raw material purchasing inventory optimization under uncertain demand, thus providing decision basis for enterprise raw material purchase inventory planning. Establishing and solving the optimization model of reducing the cost of operation and management: using the historical production data to establish the optimization model of purchasing inventory problem of iron and steel enterprises, introducing the historical data directly into the model as input parameter, The data and optimization are considered in the unified framework, and the model is solved by using the standard optimization software CPLEX, so as to make the purchasing inventory optimization decision based on historical data.
【学位授予单位】：东北大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F426.31;F274

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