基于需求特性分类的电力物资库存控制与需求预测方法研究
发布时间：2018-10-31 14:12
【摘要】：随着我国生产水平和信息化水平的逐步提高,电力相关行业对电力物资的需求日益增多,电力行业面临着客户需求多变、采购周期长、历史消耗数据缺失与失真、需求预测与库存控制困难等诸多问题,这些都给电力物资的需求管理与库存管理提出了很大挑战,因此对电力物资进行需求预测与库存控制越来越受到企业的重视。间断性需求电力物资对于企业来说至关重要,对其进行良好的需求预测与库存管理不但可以保证企业生产运营的正常进行,而且可以大大的降低库存成本,提高企业竞争力。本文以上海市电力公司某仓库运营管理实际需求为背景,从电力物资的自身特点出发,在对其需求特性进行分析与科学分类的基础上,针对库存控制问题与间断性需求预测问题展开研究,论文主要包括以下几个方面内容：(1)以上海市电力公司某仓库实际情况为背景,深入企业进行实地调研,了解整个仓库管理的一般现状,分析企业对电力物资库存管理的需求,确定本课题研究内容的重要性与可行性。以历史消耗数据为依据,提取并分析电力物资需求特性,并基于此对其进行科学全面的分类,设计了电力物资总体库存控制策略,并针对不同类型的电力物资,构建其动态库存控制模型,为实现有效的库存管理提供依据。(2)在深入了解间断性需求电力物资需求特征的基础上,将其整个预测研究工作分为两部分,即需求发生时刻预测与需求发生量预测。提出使用BP神经网络模型预测间断性需求电力物资发生时刻,并通过实验分析其优势与缺点,在此基础上提出使用遗传算法优化的BP神经网络模型进行预测。考虑间断性需求电力物资历史需求消耗数据较少的特点,提出使用灰色GM(1,1)模型进行需求发生量的预测,并通过具体预测实验说明模型的有效性及可行性,最后将两方面结合起来描述对未来的预测情况,降低了预测难度,为间断性需求电力物资的需求预测提供一种有效的方法。(3)从企业需求的角度出发,详细设计了电力物资库存控制与需求预测软件模块的总体功能及各个子模块功能,以及编程实现了包括基本数据管理、需求特性管理、需求预测以及动态库存控制等功能模块,达到了对电力物资库存进行有效控制的目的。
[Abstract]:With the gradual improvement of production level and information level of our country, the demand of electric power related industries for electric power materials is increasing day by day. The electric power industry is faced with changeable customer demand, long purchasing period, lack and distortion of historical consumption data. It is difficult to forecast the demand and control the inventory, which brings great challenge to the demand management and inventory management of electric power materials. Therefore, the enterprises pay more and more attention to the demand prediction and inventory control of electric power materials. Intermittent demand for electric power materials is very important for enterprises. Good demand prediction and inventory management can not only ensure the normal operation of enterprises, but also greatly reduce the cost of inventory and improve the competitiveness of enterprises. Based on the actual demand of a warehouse operation and management of Shanghai Electric Power Company, this paper starts from the characteristics of electric power materials, and analyzes the demand characteristics and classifies them scientifically. The paper mainly includes the following aspects: (1) taking the actual situation of a warehouse of Shanghai Electric Power Company as the background, the paper carries on the field investigation and research deeply to the enterprise, which is aimed at the inventory control problem and the intermittent demand forecasting problem. Understand the general situation of the whole warehouse management, analyze the demand of the electric power material inventory management, determine the importance and feasibility of the research content of this subject. Based on the historical consumption data, this paper extracts and analyzes the demand characteristics of electric power materials, and classifies them scientifically and comprehensively, designs the overall inventory control strategy of electric power materials, and aims at different types of power materials. The dynamic inventory control model is constructed to provide the basis for effective inventory management. (2) on the basis of deeply understanding the demand characteristics of intermittent demand, the whole prediction research work is divided into two parts. That is, demand occurrence time forecast and demand occurrence quantity forecast. In this paper, BP neural network model is used to predict the occurrence time of intermittent demand power materials, and its advantages and disadvantages are analyzed through experiments. On the basis of this, the BP neural network model optimized by genetic algorithm is proposed to forecast. Considering the fact that the historical demand data of discontinuous demand for electric power materials are less, a grey GM (1 ~ 1) model is proposed to predict the amount of demand, and the validity and feasibility of the model are illustrated by the concrete prediction experiments. Finally, the two aspects are combined to describe the forecasting situation in the future, which reduces the difficulty of forecasting, and provides an effective method for forecasting the demand of intermittent demand for electric power materials. (3) from the point of view of enterprise demand, The general function and each sub-module function of electric power material inventory control and demand prediction software module are designed in detail, and the function modules including basic data management, demand characteristic management, demand forecasting and dynamic inventory control are realized by programming. To achieve the purpose of effective control of electricity material inventory.
【学位授予单位】：东北大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TP183;F426.61;F274
，
本文编号：2302482
[Abstract]:With the gradual improvement of production level and information level of our country, the demand of electric power related industries for electric power materials is increasing day by day. The electric power industry is faced with changeable customer demand, long purchasing period, lack and distortion of historical consumption data. It is difficult to forecast the demand and control the inventory, which brings great challenge to the demand management and inventory management of electric power materials. Therefore, the enterprises pay more and more attention to the demand prediction and inventory control of electric power materials. Intermittent demand for electric power materials is very important for enterprises. Good demand prediction and inventory management can not only ensure the normal operation of enterprises, but also greatly reduce the cost of inventory and improve the competitiveness of enterprises. Based on the actual demand of a warehouse operation and management of Shanghai Electric Power Company, this paper starts from the characteristics of electric power materials, and analyzes the demand characteristics and classifies them scientifically. The paper mainly includes the following aspects: (1) taking the actual situation of a warehouse of Shanghai Electric Power Company as the background, the paper carries on the field investigation and research deeply to the enterprise, which is aimed at the inventory control problem and the intermittent demand forecasting problem. Understand the general situation of the whole warehouse management, analyze the demand of the electric power material inventory management, determine the importance and feasibility of the research content of this subject. Based on the historical consumption data, this paper extracts and analyzes the demand characteristics of electric power materials, and classifies them scientifically and comprehensively, designs the overall inventory control strategy of electric power materials, and aims at different types of power materials. The dynamic inventory control model is constructed to provide the basis for effective inventory management. (2) on the basis of deeply understanding the demand characteristics of intermittent demand, the whole prediction research work is divided into two parts. That is, demand occurrence time forecast and demand occurrence quantity forecast. In this paper, BP neural network model is used to predict the occurrence time of intermittent demand power materials, and its advantages and disadvantages are analyzed through experiments. On the basis of this, the BP neural network model optimized by genetic algorithm is proposed to forecast. Considering the fact that the historical demand data of discontinuous demand for electric power materials are less, a grey GM (1 ~ 1) model is proposed to predict the amount of demand, and the validity and feasibility of the model are illustrated by the concrete prediction experiments. Finally, the two aspects are combined to describe the forecasting situation in the future, which reduces the difficulty of forecasting, and provides an effective method for forecasting the demand of intermittent demand for electric power materials. (3) from the point of view of enterprise demand, The general function and each sub-module function of electric power material inventory control and demand prediction software module are designed in detail, and the function modules including basic data management, demand characteristic management, demand forecasting and dynamic inventory control are realized by programming. To achieve the purpose of effective control of electricity material inventory.
【学位授予单位】：东北大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TP183;F426.61;F274
，
本文编号：2302482
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