Safety Stock and Service Levels in Periodic Review Inventory Systems

The management of requirement (purchased parts and components) uncertainty in MRP systems is a serious problem for manufacturing firms. When manufacturing service levels fall below a predetermined service level, safety stock must be increased in order to adjust to the competitive environment. This paper presents the results of a set of simulation experiments in which we investigate some of the complexities of safety stock requirements, lot sizing performance and the marginal safety stock requirements associated with various service level policies. The results of the experiments have empirically shown that the marginal units of safety stock required for various service level policies follow a predictable (measurable) pattern. The research also indicates that the economic advantages of well-known dynamic lot sizing procedures are diminished by the presence of requirements uncertainty. Another important finding is the interaction between service level and ‘lumpy’ requirements. High levels of the coefficient of variation and the economic time between orders resulted in larger orders, reduced safety stock and high service levels. In general, the overall findings from this research will hopefully provide the decision maker with an in-depth understanding of the measurement and impact of various service level policies.     

A Quality Control Approach for Monitoring Inventory Stock Levels

In this paper we develop a new approach to monitor the accuracy of an inventory management system. A recorded stock level is considered accurate when the recorded level agrees with the actual stock level, otherwise there is an error. In practice, management relies on methods to measure or assure inventory accuracy not necessarily developed for this purpose. Our methodology is based on the average absolute relative difference as a simple analytical measure for inventory accuracy (AC _N ). The approach captures the status of accuracy in an inventory and allows for greater understanding of what affects inaccuracy since the theoretical measure of accuracy is composed of several parameters representing the incidence and proportion of both overstock and understock. The implementation of the methodology is constrained because complete inspection of the inventory is very expensive in most situations, so we develop the sample analogue of the accuracy measure (AC _n ) and discuss sampling strategies. The accuracy of the inventory system is monitored by incorporating AC _n into a univariate control chart.     

Stock Rationing in a Continuous Review Two-Echelon Inventory Model

In this paper we consider a 1-warehouse, N-retailer inventory system where demand occurs at all locations. We introduce an inventory model which allows us to set different service levels for retailers and direct customer demand at the warehouse. For each retailer a critical level is defined, such that a retailer replenishment order is delivered from warehouse stock if and only if the stock level exceeds this critical level. It is assumed that retailer replenishment orders, which are not satisfied from warehouse stock, are delivered directly from the outside supplier, instead of being backlogged. We present an analytical upper bound on the total cost of the system, and develop a heuristic method to optimize the policy parameters. Numerical experiments indicate that our technique provides a very close approximation of the exact cost. Also, we show that differentiating among the retailers and direct customer demand can yield significant cost reductions.     

Safety Stock Determination with Serially Correlated Demand in a Periodic-Review Inventory System

We consider a periodic-review inventory replenishment model with an order-up-to-R operating doctrine for the case of deterministic lead times and a covariance-stationary stochastic demand process. A method is derived for setting the inventory safety stock to achieve an exact desired stockout probability when the autocovariance function for Gaussian demand is known. Because the method does not require that parametric time-series models be fit to the data, it is easily implemented in practice. Moreover, the method is shown to be asymptotically valid when the autocovariance function of demand is estimated from historical data. The effects on the stockout rate of various levels of autocorrelated demand are demonstrated for situations in which autocorrelation in demand goes undetected or is ignored by the inventory manager. Similarly, the changes to the required level of safety stock are demonstrated for varying levels of autocorrelation.     

The Safety Stock Syndrome

This paper investigates the role of safety stocks in fixed order quantity-reorder point inventory systems. A common confusion over the notion of a shortage probability is shown to lead to methods which encourage excessive safety stocks. An alternative approach, proposed by R. G. Brown, is validated under quite general demand conditions. When combined with a numerical example, it is shown that negative safety stocks may be the rational response to the problem of uncertain demands, even when high levels of service are required.     

模糊需求下的库存风险及最优库存决策

分析了在模糊需求下,按经典库存模型中的经济订货批量和订货周期所导致的库存风险损失。推导了模糊需求下的经济风险函数。给出了风险函数在模糊需求分布下的重心决策方法,在此基础上得到了模糊需求下经济批量的修正公式,为模糊库存风险分析的研究提供了一种方法。     

POT模型中GPD估计方法选择及金融风险测度

极大似然、矩、概率加权矩估计是GPD参数估计的主要方法.用蒙特卡罗模拟技术产生大量GPD数据,用三种方法估计参数.通过BIAS和RMSE判断估计方法优劣,研究其随样本量和形状参数变化的差异,得到估计方法选择的标准.     

基于二层信用策略的两货栈库存模型

假设供应商向零售商提供信用支付期的同时,零售商也向顾客提供信用支付期,研究了两货栈的变质物品库存模型,并讨论了模型最优解的唯一性,最后给出了最优订购策略的算法步骤与数值例子.     

上证股指极值模型估计和VaR计算

POT极值模型参数的准确估计是计算金融资产回报厚尾分布市场风险的关键.由n阶概率加权矩得到参数的二项式回归估计,而将参数的零,一阶概率加权矩估计予以推广.极大似然估计中.将极大化似然函转化为二元函数无条件极值问题·其他参数估计方法的结果作为迭代的初始值,通过它们的似然函数值和极大似然函数值的比较以及迭代次数判断方法的优劣.实证研究表明:参数的零、一阶概率加权矩估计较接近于真值,随着阶数的提高,二项式回归参数估计的误差很大.参数的极大似然估计优于非线性回归估计优于零、一阶概率加权矩估计.在此基础上计算上证A股指数vaR值.     

Linear Model Selection Based on Risk Estimation

The problem of selecting one model from a family of linear models to describe a normally distributed observed data vector is considered. The notion of the model of given dimension nearest to the observation vector is introduced and methods of estimating the risk associated with such a nearest model are discussed. This leads to new model selection criteria one of which, called the "partial bootstrap", seems particularly promising. The methods are illustrated by specializing to the problem of estimating the non-zero components of a parameter vector on which noisy observations are available.     

Inventory Model with Supply Disruption Risk and Service Level Constraint

We. develop a newsvender model with service level constraint for one- product, and multi-supplier system, where the supplies are susceptible to disruption risks. We prove the convexity of the programming problem,and provide the neces- sary and sufficient conditions for the optimal order quantities. Through analysis or numerical experiments we observe the effects of the disrupt risk and the service level constraint on the optimal policy. We propose some managerial insights in managing the multi-source supply chain with disruption risks.     

库存影响需求下基于两层延期支付策略的供应链库存模型

研究一类货架和仓库商品共同影响需求的库存问题,采用二层延期支付策略,即供应商向零售商提供延期支付期,同时零售商也向顾客提供延期支付期;建立了相应的库存模型,得到零售商最优订购策略存在的条件及算法,最后给出数值例子和灵敏度分析.     

证券市场指数的尖峰厚尾特征与风险量估计

在对DOW,Nasdaq,S&P500和FTSE100等四个证券市场指数进行实证分析基础上,展示了证券市场指数的对数收益率具有尖峰厚尾的分布特征,并利用Logistic分布得到了很好的拟合,同时给出了基于Logistic分布的风险量VaR和CVaR的估计公式,以此计算证券市场指数的对数收益率的风险量VaR和CVaR的估计值.     

我国食品卫生安全风险评估模型

食品卫生安全关系到国计民生,建立适合于我国的食品卫生安全保障体系尤为重要.人群食物摄入量模型用"对数正态分布"估计食物摄入量分布,在对国家依据气候、地理、经济等因素进行地域划分的基础上提出了能够保证小样本空间条件下采样均匀的"层次化样本分配模型"用于采样点的选取和各采样点样本数量的分配;污染物分布模型用"贝塔分布"估计食物中的污染物分布,并采用样本在时间轴上平移的方法解决了数据在时间上的不完整性问题;风险评估模型基于人群食物摄入量和食物污染物分布模型,提出"矩元法"对污染物摄入量进行评估,并给出了模型数值化求解和右分位点确定的相关算法.实验表明,风险评估模型所确定的右分位点能有效地反映当前食品卫生安全状况.     

考虑风险偏好的动态生产库存问题的鲁棒优化模型

不同阶段需求不确定情况下,决策者的风险偏好和生产过程中的废品处理影响着供应链生产库存管理和供应链整体效益。本文考虑决策者风险偏好下,构建了包含I个生产者企业,一个库存点和一个废物处理基地的T阶段动态供应链生产库存框架,建立了椭球型需求不确定集下,以追求整体收益最大化为目标的不确定优化模型,并应用鲁棒优化理论得到了数据确定性线性鲁棒对应模型,讨论了模型解的可靠性和有效性。最后的算例表明,只有当决策者风险偏好参数在一定范围内时,才会存在满足条件且具有较高可靠性的鲁棒决策,验证了该鲁棒优化模型的合理性。     

基于二层信用支付的变质物品库存模型

基于时变需求的库存问题一直是库存管理者关注的重点之一,大多数基于二层信用支付的库存模型都是假设需求率为常数.假设需求率是时间的指数函数,建立了二层信用支付条件下的变质物品库存模型,并证明了最优解是存在且唯一的,给出了确定最优补货策略的算法步骤,最后通过数值例子对主要参数进行了灵敏度分析.     

基于风险约束的套期保值模型及沪深300股指实证研究

提出利用风险价值VaR建立套期保值资产组合的风险约束.以套期保值资产组合收益最大为目标,以控制套期保值资产组合风险为约束,建立了基于风险约束的套期保值模型.该模型在有效控制风险的基础上,可以大幅提高套期保值资产组合的收益.对沪深300股指现货和期货的数据进行了实证分析,对比了现有研究的最小二乘((OLS)、向量自回归(VAR)、向量误差修正(VEC)三种模型以及本文建立的基于风险约束的期货套期保值模型.样本内检验结果表明,本模型比现有研究模型的收益有大幅提高,平均增加81.6%.同时并没有失去对风险的控制,与现有研究模型只有5.32%的差别.对于样本外检验,模型在控制风险和提高收益两个方面都要优于现有研究模型.模型比现有研究模型平均可提高收益21.4%,平均降低风险3.61%.     

GARCH模型估计方法选择及对上证指数的应用

本文介绍了对ARCH/GARCH模型的两种估计方法:准极大似然估计和极小绝对偏差估计,并提出了一种基于自助法(Bootstrap)对估计方法的选择。在厚尾程度不同的情况下进行了模拟分析,表明对于一个具体的数据,该选择法能够自动选择较优的估计方法。并用该方法对上海证券交易所A股和B股的股价指数进行了分析,印证了上海股市B股收益率的尾部厚于A股收益率尾部。     

APARCH 模型在证券投资风险分析中的应用

本首先描述金融时间序列的一般特性，从收益率的波动性与分布两方面进行考虑，建立起计算时变风险值的VaR—APARCH模型，并应用VaR—APARCH模型在多种分布情形下测算了上证综合指数的风险，结果表明基于GED分布的VaR—APARCH模型能够较好地刻画高频时间序列的尖峰肥尾性及杠杆效应等特性。     

基于DCC-Copula-SV-M-t模型的股市系统性风险溢出分析

考虑到股市系统性风险溢出的时变性和联动性,本文融合SV-M-t模型和Copula理论,构建DCC-Copula-SV-M-t模型,利用蒙特卡洛马尔科夫(MCMC)算法估计模型参数,得到了系统性风险溢出量的计算方法。接着以上证综合指数、深证成分指数,恒生指数和标普500指数为代表的系统重要性股市为实证样本。结果表明:模型参数估计的MCMC方法可行且具有较为明显的优势。该模型能较好地度量系统重要性股市风险溢出的非对称性。沪股具有重要的引导地位,美股风险溢出影响有限。本文所构建的模型丰富了股市系统性风险度量与管理的新工具。