一类动态库存与排产优化问题的研究与应用
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摘要
本文在对国内外相关文献进行归纳总结的基础上,以宝钢包装钢带有限公司的生产实践为研究背景,建立了基于客户忠诚度的销量预测模型,考虑到多项约束条件建立了生产排产模型并进行仿真求解,提出了根据热轧原材料的价格、与订单相关的时间及订货量三个特征对热轧原料进行分类管理的策略。具体工作有：
(1)首次将数据挖掘中的决策树方法应用于客户忠诚度分析,给出了这一方法的基本算法和对客户忠诚度分析的具体步骤。结合公司的客户数据进行了实例分析,得到了公司的客户属性特征和忠诚度高低的分类规则。采用时间序列模型对公司的产品销售记录进行信息挖掘,给出公司下一个销售周期的各种产品销售量的初步预测值。同时,结合客户的忠诚度信息,设置“稳定系数”对各种产品销售量的初步预测值进行修正,获得销售量的最终预测值,从而为公司产品库存结构的确定提供决策支持,进而为确定单个生产周期内产品的生产产量比例提供依据。
(2)基于企业的订单及市场预测,结合新旧生产线的产能和各个产品的相关参数(如产品产量、产品售价、生产时间、调整时间、库存量等指标),考虑不同规格品种的生产效率、工艺约束等约束条件,在确保交货期的前提下,以实现均衡生产、产成品产量最大化为优化目标,运用优化理论建立了用于解决混合生产线排产问题的模型。建立设备库、产品库、零件库、工艺库、工时定额库等加工基础数据库,提出合理有效的计划排产方法,并且采用LINGO软件开发了相应的软件系统,对排产模型仿真求解。仿真结果验证了算法的可行性,较好地解决了生产调度问题。
(3)根据公司的原材料采购及库存管理的实际情况,以产品订单为核心,按照原材料价格走势、订单时间、订货量这三个特征对原材料进行分类,共分为四类。根据各类原材料的具体特征,分别确定出最优订货批量与再订货点,从而制定出相应的采购与库存策略,来指导公司的采购行为与库存控制。以公司提供的2005年部分原材料、产品相关资料为数据源,进行策略分析和检验。示例计算结果表明,文中建立的模型是正确、合理的,制定的策略是可行、可靠的。
论文最后指出了今后进一步研究的问题和方向。
This paper carries on the induction and the summary to the correlated domestic and overseas research; at the background of the manufacture practice of Packaging Material Company of Baosteel International, the sales forecasting model which is based on the costumer loyalty is set up. Considering a series of restriction conditions, the product scheduling model is found and the simulation method is used to solve the model. The classifying management strategy to the hot- rolling material is proposed which is based on the price of the material, the duration of the orders and the quantities of the orderings. The details are as follows.
(1) The decision tree method in data mine is used on the analysis of the costumer loyalty for the first time; the basic algorithm is given and the arithmetic steps are shown; the case study is done on the data of the costumers; the characteristics of the costumers and the rules of classify to the loyalty are found. The time series model is used to analyze the production sale record of the company; the estimated sales of different kinds of productions during the next sale cycle are provided. At the same time, combined the information of the costumer loyalty, the "stable coefficient" is set to modify the forecasting numbers; the modified numbers are used as the final forecasting ones which are used as the decision support of the production inventory structure, and then the product plan in a single cycle could be made.
(2) Taking the equilibrium manufacture and the optimization of the output as the object function and using the optimizing theory, the mix-manufacture-line scheduling model is set up; the foundation of the model which could promise the delivery is based on the orders and the forecast of the market, and the following factors are considered: the capacity of all manufacture lines, the parameters of different productions (such as the yield, the price, the duration, the modified period, the inventory and so on), the manufacture efficiency of different categories, the arts and crafts. The basic databases of manufacture are set up such as equipment database, production database, accessory database, the arts and crafts database, man-hour quota database and so on; the reasonable and effective manufacture scheduling method is proposed and the LINGO software is used to simulate the model; the simulation result shows the feasibility of the algorithm and the scheduling problem is well solved.
(3) Considering the practical circumstance of the raw materials procurement and inventory management of the company and basing on the product orders, the raw materials are classified into four groups according to the following characteristics:the variation trend of the total price of raw materials, the duration of the orders and the quantities of ordering. According to the characteristics of each group, the optimal production batch size and re-order-point are given and the procurement and inventory strategies are made to supervise the activities of the company. Taking the raw materials and orders information in 2005 supplied by the company as the data source, the analysis and testing are made. The illustrated example shows the creativity and rationality of the model and the feasibility and reliability of the strategies.
At last, the problems needed to be considered further are proposed and further research directions are pointed.
(1)首次将数据挖掘中的决策树方法应用于客户忠诚度分析,给出了这一方法的基本算法和对客户忠诚度分析的具体步骤。结合公司的客户数据进行了实例分析,得到了公司的客户属性特征和忠诚度高低的分类规则。采用时间序列模型对公司的产品销售记录进行信息挖掘,给出公司下一个销售周期的各种产品销售量的初步预测值。同时,结合客户的忠诚度信息,设置“稳定系数”对各种产品销售量的初步预测值进行修正,获得销售量的最终预测值,从而为公司产品库存结构的确定提供决策支持,进而为确定单个生产周期内产品的生产产量比例提供依据。
(2)基于企业的订单及市场预测,结合新旧生产线的产能和各个产品的相关参数(如产品产量、产品售价、生产时间、调整时间、库存量等指标),考虑不同规格品种的生产效率、工艺约束等约束条件,在确保交货期的前提下,以实现均衡生产、产成品产量最大化为优化目标,运用优化理论建立了用于解决混合生产线排产问题的模型。建立设备库、产品库、零件库、工艺库、工时定额库等加工基础数据库,提出合理有效的计划排产方法,并且采用LINGO软件开发了相应的软件系统,对排产模型仿真求解。仿真结果验证了算法的可行性,较好地解决了生产调度问题。
(3)根据公司的原材料采购及库存管理的实际情况,以产品订单为核心,按照原材料价格走势、订单时间、订货量这三个特征对原材料进行分类,共分为四类。根据各类原材料的具体特征,分别确定出最优订货批量与再订货点,从而制定出相应的采购与库存策略,来指导公司的采购行为与库存控制。以公司提供的2005年部分原材料、产品相关资料为数据源,进行策略分析和检验。示例计算结果表明,文中建立的模型是正确、合理的,制定的策略是可行、可靠的。
论文最后指出了今后进一步研究的问题和方向。
This paper carries on the induction and the summary to the correlated domestic and overseas research; at the background of the manufacture practice of Packaging Material Company of Baosteel International, the sales forecasting model which is based on the costumer loyalty is set up. Considering a series of restriction conditions, the product scheduling model is found and the simulation method is used to solve the model. The classifying management strategy to the hot- rolling material is proposed which is based on the price of the material, the duration of the orders and the quantities of the orderings. The details are as follows.
(1) The decision tree method in data mine is used on the analysis of the costumer loyalty for the first time; the basic algorithm is given and the arithmetic steps are shown; the case study is done on the data of the costumers; the characteristics of the costumers and the rules of classify to the loyalty are found. The time series model is used to analyze the production sale record of the company; the estimated sales of different kinds of productions during the next sale cycle are provided. At the same time, combined the information of the costumer loyalty, the "stable coefficient" is set to modify the forecasting numbers; the modified numbers are used as the final forecasting ones which are used as the decision support of the production inventory structure, and then the product plan in a single cycle could be made.
(2) Taking the equilibrium manufacture and the optimization of the output as the object function and using the optimizing theory, the mix-manufacture-line scheduling model is set up; the foundation of the model which could promise the delivery is based on the orders and the forecast of the market, and the following factors are considered: the capacity of all manufacture lines, the parameters of different productions (such as the yield, the price, the duration, the modified period, the inventory and so on), the manufacture efficiency of different categories, the arts and crafts. The basic databases of manufacture are set up such as equipment database, production database, accessory database, the arts and crafts database, man-hour quota database and so on; the reasonable and effective manufacture scheduling method is proposed and the LINGO software is used to simulate the model; the simulation result shows the feasibility of the algorithm and the scheduling problem is well solved.
(3) Considering the practical circumstance of the raw materials procurement and inventory management of the company and basing on the product orders, the raw materials are classified into four groups according to the following characteristics:the variation trend of the total price of raw materials, the duration of the orders and the quantities of ordering. According to the characteristics of each group, the optimal production batch size and re-order-point are given and the procurement and inventory strategies are made to supervise the activities of the company. Taking the raw materials and orders information in 2005 supplied by the company as the data source, the analysis and testing are made. The illustrated example shows the creativity and rationality of the model and the feasibility and reliability of the strategies.
At last, the problems needed to be considered further are proposed and further research directions are pointed.
引文
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