A Bayesian approach to demand estimation and inventory provisioning

This article addresses the problem of explicitly taking into account uncertainty about the demand for spare parts in making inventory procurement and stockage decisions. The model described provides for a unified treatment of the closely related problems of statistical estimation of demand and resource allocation within the inventory system, and leads to an easily implemented, efficient method of determining requirements for spare parts both in the early provisioning phase and in later periods of operations when demand data have accumulated Analyses of the model's theoretical foundations and of sample outcomes of the model based upon data on parts intended for use in the F-14 lead to conclusions of great importance to both support planners and operations planners Finally, of particular significance is the ability afforded the planner by this model to quantify the impact on inventory system costs of varying levels of system reliability or management uncertainty as to projected system performance. This will provide an economic basis for analysis of such alternatives as early deployment, operational testing, and equipment redesign.     

Bayesian estimation and optimal designs in partially accelerated life testing

A method of life testing is proposed which combines both ordinary and accelerated life-testing procedures. It is assumed that an item can be tested either in a standard environment or under stress. The amount of stress is fixed in advance and is the same for all items to be tested However, the time x at which an item on lest is taken out of the standard environment and put under stress can be chosen by the experimenter subject to a given cost structure. When an item is put under stress its lifetime is changed by the factor α. Let the random variable T denote the lifetime of an item in the standard environment, and let γ denote its lifetime under the partially accelerated test procedure just described. Then Y = T if T ≦ x, and Y = x + α (T > x) if T > x. It is assumed that T has an exponential distribution with parameter θ. The estimation of θ and α and the optimal design of a partially accelerated life test are studied in the framework of Bayesian decision theory.     

Design and estimation for small sample sensitivity testing

In sensitivity testing for the Department of Defense, the high cost of experimental units necessitates the use of small sample sizes and accentuates the importance of design. This article compares five data collection-estimation procedures. Four of these are modifications of the Robbins-Monro method, and the other is the Langlie. The simulation study is designed as a factorial experiment with response function, sample size, initial design point, gate width, and noise as factors. The estimated V₅₀ and its MSE are the responses compared to assess the small sample behavior of each method. Although there is no single clear-cut winner, the Delayed Robbins-Monro (DRM) with maximum likelihood estimation and the Estimated Quantal Response Curve (Wu [21]) are shown to perform well over a broad variety of conditions.     

威布尔分布场合下无失效数据的Bayes分析

通过对分布函数进行变换,使变换后的函数成为凹函数,利用凹函数性质给出了各检测时刻失效概率的Bayes估计,进而得到了产品可靠性指标的估计。最后,通过对实际数据进行计算,验证了方法的稳定性。     

A graphical aid for sensitivity analysis of estimated regression coefficients

A problem often arising in applied linear regression modeling is determining the appropriate weight to attach to each observation. In the extreme, the problem extends to the deletion of observations from a data base. Since the choice of weights, fitting criteria, and estimation procedure depend on the specific objectives of the modeling, universally applicable guidelines are virtually nonexistent. However, the sensitivity of analytic conclusions to weights assigned to “suspect” observations can be conveniently assessed using a graphical display. This report develops such a display based on a modeling of outliers which leads naturally to estimators based on a weighted least-squares criterion, and a data-analytic method for determining how much downweighting to impose on a specific subset of observations. This technique is illustrated with several examples, including one relating air pollution to human mortality.     

Warranty analysis and renewal function estimation

Estimation of the expected cost of a warranty for a stochastically failing unit is closely tied to estimation of the renewal function. The renewal function is a basic tool also used in probabilistic models arising in other areas such as reliability theory, inventory theory, and continuous sampling plans. In these other areas, estimation of a straight line approximation of the renewal function instead of direct estimation of the renewal function has proved successful. This approximation is based on a limit expression for large values of the argument, say t, of the renewal function. However, in warranty analusis, typically t is small compared to the mean failure time of the unit. Hence, alternative methods for renewal function estimation, both parametric and nonparametric, are presented and discussed. An important aspect of this paper is to discuss the performance of the renewal function estimators when only a small number of failed units is available. A Monte Carlo study is given which suggests guidelines for choosing an estimator under various circumstances.     

A Bayesian analysis on the effect of multiple supply options in a quick response environment

In the apparel industry, vendors often suffer from high mismatches in supply and demand. To cope with this problem, they procure the same style product from different suppliers with different manufacturing costs. Especially in the quick response environment, which allows vendors to monitor trends in customer demand and search for available suppliers through the electronic market, they have additional opportunities to improve their decision‐making. In this paper, we propose an analytical profit maximization model and develop efficient decision tools to help both the middle and lower level managers pursuing this strategy. Furthermore, we have shown how significantly the vendors' potential competitive edge can be improved by exploiting multiple supply options, even at the expense of high premium procurement costs for late orders. The effect is critical, especially in a highly competitive market, and it has important implications for the top managers. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

Generalized linear programming and sensitivity analysis techniques

In this article we report on numerical experiments conducted to assess the performance of c-programming algorithms for generalized linear programming problems involving the maximization of composite-convex objective functions. The results indicate that the standard parametric sensitivity analysis techniques of the simplex method can play a central role in such algorithms. We also comment on issues concerning the use of commercial LP packages to solve problems of this type. © 1996 John Wiley & Sons, Inc.     

Reliability sensitivity analysis based on multi-hyperplane combination method

For a nonlinear limit state function, the first-order reliability method (FORM) may cause large errors in the computation of not only the reliability index or failure probability but also the reliability sensitivity. In order to obtain more the accurate results of the reliability sensitivity analysis, a number of hyperplanes are built near the design point by first-order Tayler series expansion, which replace the known nonlinear limit state hypersurface, and an equivalent computational method is utilized to construct an equivalent hyperplane of the obtained hyperplanes. And the reliability sensitivities can be estimated more accurately by the derived equations based on the equivalent hyperplane. An example shows that the method is effective and feasible.     

A robust regression technique using compound estimation

Least squares fitting of regression models is a widely used technique. The presence of outliers in the data can have an adverse effect on the method of least squares, resulting in a model that does not adequately fit to the bulk of the data. For this situation, robust regression techniques have been proposed as an improvement to the method of least squares. We propose a robust regression procedure that performs well relative to the current robust methods against a variety of dataset types. Evaluations are performed using datasets without outliers (testing efficiency), with a large percentage of outliers (testing breakdown), and with high leverage outliers (testing bounded influence). The datasets are based on 2-level factorial designs that include axial points to evaluate leverage effects. A Monte Carlo simulation approach is used to evaluate the estimating capability of the proposed procedure relative to several competing methods. We also provide an application to estimating costs for government satellites. © 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 125–139, 1998     

成败型产品的Bayes鉴定试验方案研究

利用可靠性增长模型给出了成败型产品鉴定试验的一种Bayes方法.提出了Bayes鉴定试验的最大后验风险准则,利用这种准则制定的鉴定试验方案综合了产品研制过程中的先验信息.在确保产品质量的前提下,与传统的鉴定试验方案相比,将大大节省试验时间.     

确定舰艇备件携带量的贝叶斯方法

本文针对一些舰艇的小子样特点,推出了确定其备件携带量的贝叶斯方法。     

On the design of a tandem queue with blocking: Modeling,analysis, and gradient estimation

We demonstrate here how recent advances in the study of discrete-event stochastic systems provide fruitful results for the modeling, analysis, and design of manufacturing systems. We consider a multistage make-to-stock system where outputs from the final stage are used to satisfy customer demands. We address the problem of finding the appropriate trade-off between reduced order waiting time and increased process speeds. Using the idea of infinitesimal perturbation analysis (IPA), we establish a simple procedure where sample-path derivatives can be obtained along an arbitrary sample path. Under suitable conditions, we demonstrate that these derivative estimators are unbiased and strongly consistent and can be used in a classical stochastic optimization scheme to solve the problem. The role of continuity and convexity on the validity of the estimator is also addressed. Although the focus of this article is not to solve for the optimal solution, we provide a theoretical justification for such a pursuit. The approach is appealing as it is numerically stable, easy to implement, and can be extended to other system performance measures. © 1994 John Wiley & Sons, Inc.     

An approach to postoptimality and sensitivity analysis of zero-one goal programs

In this article we present a methodology for postoptimality and sensitivity analysis of zero-one goal programs based on the set of k-best solutions. A method for generating the set of k-best solutions using a branch and bound algorithm and an implicit enumeration scheme for multiple objective problem are discussed. Rules for determining the range of parameter changes that still allows a member of the k-best set to be optimal are developed. An investigation of a sufficient condition for postoptimality analysis is also presented.     

成败型产品验收试验方案研究

在可靠性定型试验的基础上,利用多层贝叶斯方法确定批产品可靠性指标的先验分布,从而制定出成败型产品可靠性验收试验的一种贝叶斯方案.给出利用定型试验信息确定产品可靠性指标先验分布的方法.这种验收方法充分利用了产品定型试验中的先验信息,在确保有较好验收效果的前提下,与传统的验收试验相比,可以大大减少试验量,从而得到可观的经济效益.     

聚合物封装光纤光栅动态声压增敏有限元分析

采用有限元法对先纤光栅圆柱型封装结构的动态声压增敏效果进行了分析.结果表明:为使光纤光栅的应变均匀一致,光栅应放在正中间位置,且封装材料应足够长.在动态声压作用下,聚合物的泊松比越小,聚合物的杨氏模量越小,光纤光栅的动态声压的灵敏度越高.随着聚合物外径的增加,光纤光栅的动态声压的灵敏度逐步提高.但当封装聚合物的外径增加...     

Remittances and terrorism: A global analysis

This paper is the first global investigation of the relationship between remittances and terrorism. To discern this relationship, we draw terrorism event data from the Global Terrorism Database and International Terrorism: Attributes of Terrorism Events. When a host of standard terrorism controls is employed, lagged remittances as a share of gross domestic product have a positive and significant impact on both domestic and transnational terrorist attacks. For the venue country’s viewpoint, lagged remittances have a greater marginal impact on domestic than on transnational terrorism. However, when we investigate remittances to the home country of the perpetrator, lagged remittances have the greatest marginal impact on transnational terrorism. Throughout our investigation, standard terrorism controls perform according to our priors and those of the literature, lending credence to the isolation of the impact of remittances. We also account for endogeneity concerns.     

Parallel machine scheduling: A probabilistic analysis

The minimum makespan of the general parallel machine scheduling problem with m machines and n jobs is studied. As for a number of other important combinatorial problems, the theory of empirical processes proves to be a very elegant and powerful tool for the probabilistic analysis of the solution value. It is used in this paper to derive a scheduling constant θ such that, for random processing times, the minimum makespan almost surely grows as θn when n goes to infinity. Moreover, a thorough probabilistic analysis is performed on the difference between the minimum makespan and θn. Explicit expressions for the scheduling constant are given for an arbitrary number of unrelated machines with identically distributed processing times (with an increasing failure rate), and for an arbitrary number of uniform machines and generally distributed processing times. © 1996 John Wiley & Sons, Inc.