基于多重指标下ABC分类法的煤矿库存物资分类

传统的ABC分类法基于年销售额单一度量标准,容易忽视其它影响库存物资的因素。鉴于此,本文应用多重指标的ABC分类法对郑州煤电物资供销公司的库存物资进行分类。文中比较了两个指标(月平均使用金额与提前期)、三个指标(月平均使用金额、月平均单位库存成本或月平均单位成本与提前期)及五个指标(月平均使用数量、提前期、供应商数量、月平均单位库存成本、月平均销售成本)的分类效果,另外,提前期的取值也分别采用最大值、最小值、平均值进行了计算。与现场管理者的经验值比较,结果表明采用两个指标(月平均使用金额与提前期)且提前期取最小值的吻合效果最好。本研究成果可应用于煤矿物资的分类,可根据具体实际情况,添加度量物资重要性的指标。     

未确知测度模型在建筑节能方案评价中的应用

建筑节能方案评价是一个涉及多因素的系统工程,目前常用的单一指标评价并不能对节能方案的推广起至应有作用,根据我国能源政策设计了一套多指标综合评价体系.给出了一种定量化描述建筑节能方案评价指标的方法,建立了基于未确知测度的评价模型,并通过信息熵确立指标的分类权重,明显优于过去常用的AHP确定权重的主观判断方法,具有更高的科学性和实际应用价值,有利于优秀节能技术的扩散.     

评估指标关联性因素分析方法研究

评价指标的关联性是评价指标体系设计中常遇到且不易解决的问题.本文提出因素分析的方法对评价指标进行关联性分析,对指标进行筛选和合并,建立科学合理的评价指标体系.     

运用Matlab的线性供应链仿真控制策略研究

由于供应链终端需求的不确定性,需求信息在向上级传递过程中逐渐放大,容易造成"牛鞭效应".通过分析线性供应链的系统特征,并研究其稳定性的条件,并运用不同的策略,对其进行仿真模拟,结果表明:综合考虑近邻、次近邻的库存需求和终端消费者的需求变化时各供应商的库存波动得到明显的改善.在仿真模拟结果中,最大库存波动值是2.48,且考虑终端消费者的权重是0.248时,波动消失,说明最大库存波动值对终端消费者的敏感性较强,结果表明改进后的策略能抑制牛鞭效应对供应商库存波动的影响.     

一种改进企业在框架协议下库存管理的方法

企业为了货源的稳定而与供应商签订一定期限内的订购框架协议,但如何实施订购策略以保障协议量的完成,保证满足需求的同时最小化企业的库存成本成为企业必须考虑的一个问题.传统的企业库存管理方法如(r,Q)、(s,S)等订购策略在一定程度上只考虑了如何满足需求,避免缺货,而没有考虑供应商的供货能力,在协议期内的总订购量只考虑了需求的影响,因而不能保证框架协议的完成.本文在(s,S)策略的基础上,考虑了框架协议的约束,提出了一种既能够保障框架协议的完成,又能够最大限度满足需求,同时降低企业库存成本的方法一“双表作业法”,并验证了方法的有效性.     

考虑季末调整的季节性产品(Qi,Ri)库存模型与管理

考虑季节性产品需求的季节性周期变化、季节内需求不确定性双重波动对产品需求的影响,为季节性产品进行综合需求预测,制定库存管理策略提供参考.本研究综合Holt-Winter需求预测模型和(Q,R)库存模型进行订货点和订货量的决策,并针对季节性产品特点提出了季节间转换时期的订货策略.最后,利用上述模型和某化工企业多年实际数据,进行实证研究,对化工产品的订货量和订货点进行优化,验证了本研究提出的模型与方法可以大幅降低季节性产品库存成本和缺货率.研究对季节性产品库存管理有着重要的学术与实践意义.     

指标体系的构建原理与评价方法研究

针对目前指标体系在构建和评价方面缺乏统一理论与方法这一现状,在不考虑具体评价问题的基础上,对一般意义上的指标体系进行了构建原理与评价方法研究.从时间维、方法维和逻辑维三方面对构建方法进行了阐述;建立了指标体系的数学模型,并提出了基于正交实验设计的指标权重计算方法;以合理指标体系的基本要素为依据,定量地分析了体系的完备性和指标间的相关性.     

基于混合高斯模型的指标优化方法

借鉴混合高斯模型的方法,提出了基于混合高斯模型的非参数检验法用于评价指标体系的构建.首先运用混合高斯模型对现有指标体系进行聚类分析,然后运用非参数检验的秩相关系数对分类后的指标体系进行筛选,最终确定评价指标体系的构成,保证指标体系的全面性和代表性.实例结果表明,方法分类精度高、简便、实用,在指标优化中具有应用价值.     

同一水平下模糊规则信息熵的描述

给出了模糊知识系统及模糊决策逻辑公式的定义,在此基础上描述了模糊决策逻辑公式及模糊知识系统下模糊规则的信息熵,讨论了模糊规则信息熵的相关性质;其次,利用模糊规则信息熵对模糊规则进行了分类、评价,从而为建立合理的模糊系统提供了一种有效的判定方法;最后,通过实例验证了所提出理论的正确性.     

ARMA(1,1)需求条件下供应链需求提前承诺的影响效果分析

为了分析供应链需求提前承诺的影响效果,考虑供应链所面临的顾客需求满足ARMA（1,1）过程。首先从理论上建立正常顾客需求与顾客需求提前承诺时零售商订单量波动程度和平均库存的定量描述模型,通过两种情形下的比较分析,得出在顾客需求自回归系数大于零时,顾客需求提前承诺将减小牛鞭效应和平均库存水平;同时得出在顾客需求提前承诺时,如果顾客需求自回归系数大于零,顾客提前承诺的需求比例越高,则牛鞭效应和平均库存水平越低;顾客需求提前承诺的时间跨度越长,则牛鞭效应和平均库存水平也越低。反之亦然。其次运用仿真方法分析了顾客需求提前承诺对零售商平均库存成本的影响,得出在顾客需求自回归系数大于零时,顾客需求提前承诺将有效降低零售商的平均库存成本。     

A note on multi-criteria ABC inventory classification using weighted linear optimization

Ramanathan [R. Ramanathan, ABC inventory classification with multiple-criteria using weighted linear optimization, Computers & Operations Research 33 (2006) 695–700] recently proposed a weighted linear optimization model for multi-criteria ABC inventory classification. Despite its many advantages, Ramanathan’s model (R-model) could lead to a situation where an item with a high value in an unimportant criterion is inappropriately classified as a class A item. In this paper we present an extended version of the R-model for multi-criteria inventory classification. Our model provides a more reasonable and encompassing index since it uses two sets of weights that are most favourable and least favourable for each item. An illustrative example is presented to compare our model and the R-model.     

Management of multicriteria inventory classification

The most common method that materials managers use for classifying inventory items for planning and control purposes is the annual-dollar-usage ranking method (ABC classification). Recently, it has been suggested that multiple criteria ABC classification can provide a more comprehensive managerial approach, allowing consideration of other criteria such as lead time and criticality. This paper proposes the use of the Analytical Hierarchy Process (AHP) to reduce these multiple criteria to a univariate and consistent measure to consider multiple inventory management objectives.     

An improvement to multiple criteria ABC inventory classification

In this paper we presented an extended version of the Ng-modelg [W.L. Ng, A simple classifier for multiple criteria ABC analysis, European Journal of Operational Research 177 (2007) 344–353] for multi-criteria inventory classification. The proposed model is a nonlinear programming model which determines a common set of weights for all the items. Our model not only incorporates multiple criteria for ABC classification, but also maintains the effects of weights in the final solution, an improvement over the model proposed by Ng. An illustrative example is presented to compare our model and the Ng-model.     

A regression-based improvement to the multiple criteria ABC inventory classification analysis

Annals of Operations Research - The aim of this paper is to propose a regression-based approach for obtaining a set of weights for multi-criteria ABC inventory analysis, which differ across...     

A simple classifier for multiple criteria ABC analysis

To have an efficient control of a huge amount of inventory items, traditional approach is to classify the inventory into different groups. Different inventory control policies can then applied to different groups. The well-known ABC classification is simple-to-understand and easy-to-use. However, ABC analysis is based on only single measurement such as annual dollar usage. It has been recognized that other criteria are also important in inventory classification.     

Towards a normative model for inventory cost management in a generalized ABC classification system

This paper establishes a general ABC inventory classification system as the foundation for a normative model of the maintenance cost structure and stock turnover characteristics of a large, multi-item inventory system with constant demand. For any specified number of inventory classes, the model allows expression of the overall system combined ordering and holding cost in terms of (i) the re-ordering frequencies for the items in each inventory class and (ii) the inventory class structure, that is, the proportion of the total system's items that are in each inventory class. The model yields a minimum total maintenance cost function, which reflects the effect of class structure on inventory maintenance costs and turnover. If the Pareto curve (a.k.a. Distribution-by-value function) for the inventory system can be expressed (or approximated) analytically, the model can also be used to determine an optimal class structure, as well as an appropriate number of inventory classes. A special case of the model produces a simply structured, class-based ordering policy for minimizing total inventory maintenance costs. Using real data, the cost characteristics of this policy are compared to those of a heuristic, commonly used by managers of multi-item inventory systems. This cost comparison, expressed graphically, underscores the need for normative modelling approaches to the problem of inventory cost management in large, multi-item systems.     

MACBETHSort: a multiple criteria decision aid procedure for sorting strategic products

Efficient companies need to know which their strategic products are. For this purpose, the ABC classification based on the item’s value was developed and was used for a long time. Later, it was recognised that several other criteria need to be considered and multi-criteria ranking methods were applied. However, the classes have always been defined based only on a relative proportion. Therefore, the number of products in a class is independent of the actual importance of the products. In this paper, a new sorting procedure MACBETHSort is introduced, which is an evolution of the choice, ranking and rating technique MACBETH. The procedure has been validated in a real case study for assigning access and entrance solutions in ABC classes.     

双向替代产品库存模型研究

运用最优控制理论和数理经济学方法研究了供应链管理时代下广泛存在的双向替代产品的最优库存问题,建立了利润最大化前提下的双向替代品的库存模型,证明了该问题解的存在性,并给出了求解最优订货量的方法步骤,可为实施有效的库存管理、降低企业的物流成本提供借鉴.     

基于熵权TOPSIS-PSO-ELM的制造企业绿色创新能力评价模型及实证研究

为客观和准确地评价制造企业绿色创新能力,本文构建了制造企业绿色创新能力评价指标体系,提出了基于熵权TOPSIS的粒子群(PSO)优化极限学习机(ELM)集成学习算法的制造企业绿色创新能力评价模型。首先运用熵权法客观确定指标权重,结合TOPSIS测度并综合评价制造企业绿色创新能力,然后将评价值作为先验样本进行极限学习机的训练与测试,训练过程中利用PSO优化极限学习机的网络结构与连接权值,从而对绿色创新能力进行全面的分析和评价。最后以60家制造企业为例进行实证分析,并将熵权TOPSIS-PSO-ELM算法与极限学习机回归拟合算法对比,结果表明:基于熵权TOPSIS-PSO-ELM模型所得评价结果较已有方法更为准确可靠。此外,为进一步提高我国制造企业绿色创新发展能力提出了理论建议。     

智能电表最优更换及备件库存联合决策

智能电表是智能电网运行的关键部件,提高其可靠性和可用度对保证电力的持续不间断供应和准确电能测量至关重要。充足的智能电表库存是其换装与维修的基本保障。本文基于智能电表的故障特性和换装需求分析,建立了智能电表的最优更换与备件库存联合决策模型,并给出了优化方法,以求得可以使系统长期平均运营成本最小的最优更换与备件库存策略。