Optimal service rates of a service facility with perishable inventory items

In this paper we optimally control service rates for an inventory system of service facilities with perishable products. We consider a finite capacity system where arrivals are Poisson‐distributed, lifetime of items have exponential distribution, and replenishment is instantaneous. We determine the service rates to be employed at each instant of time so that the long‐run expected cost rate is minimized for fixed maximum inventory level and capacity. The problem is modelled as a semi‐Markov decision problem. We establish the existence of a stationary optimal policy and we solve it by employing linear programming. Several numerical examples which provide insight to the behavior of the system are presented. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 464–482, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10021     

Two‐stage component test plans for testing the reliability of a series system

A system reliability is often evaluated by individual tests of components that constitute the system. These component test plans have advantages over complete system based tests in terms of time and cost. In this paper, we consider the series system with n components, where the lifetime of the i‐th component follows exponential distribution with parameter λ_i. Assuming test costs for the components are different, we develop an efficient algorithm to design a two‐stage component test plan that satisfies the usual probability requirements on the system reliability and in addition minimizes the maximum expected cost. For the case of prior information in the form of upper bounds on λ_i's, we use the genetic algorithm to solve the associated optimization problems which are otherwise difficult to solve using mathematical programming techniques. The two‐stage component test plans are cost effective compared to single‐stage plans developed by Rajgopal and Mazumdar. We demonstrate through several numerical examples that our approach has the potential to reduce the overall testing costs significantly. © 2002 John Wiley & Sons, Inc. Naval Research Logistics, 49: 95–116, 2002; DOI 10.1002/nav.1051     

Threshold optimization for weighted voting classifiers

Weighted voting classifiers considered in this paper consist of N units each providing individual classification decisions. The entire system output is based on tallying the weighted votes for each decision and choosing the one which has total support weight exceeding a certain threshold. Each individual unit may abstain from voting. The entire system may also abstain from voting if no decision support weight exceeds the threshold. Existing methods of evaluating the reliability of weighted voting systems can be applied to limited special cases of these systems and impose some restrictions on their parameters. In this paper a universal generating function method is suggested which allows the reliability of weighted voting classifiers to be exactly evaluated without imposing constraints on unit weights. Based on this method, the classifier reliability is determined as a function of a threshold factor, and a procedure is suggested for finding the threshold which minimizes the cost of damage caused by classifier failures (misclassification and abstention may have different price.) Dynamic and static threshold voting rules are considered and compared. A method of analyzing the influence of units' availability on the entire classifier reliability is suggested, and illustrative examples are presented. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 322–344, 2003.     

Controlling rates in a double queue

A double-ended queue with a Poisson arrival pattern is examined in a situation where the rates depend (in a restricted sense) on both the time and the state of the system. Under some circumstances, the rates can be controlled. This article studies the distribution of the difference in queue sizes for each member of a large class of control strategies and introduces the problem of determining the optimal times at which the control should be in effect in order to maximize certain objective functions.     

The relationship between material failures and flight hours

If material failures follow a Poisson distribution, then the expected number of failures is exactly proportional to flight hours. However, this article demonstrates that proportionality will not be revealed by simple correlation or regression analysis between monthly flight hours and the number of monthly failures. To test for proportionality, one must instead test the underlying hypothesis that the data follow a Poisson distribution. This article presents three simple tests that may be used for this purpose. The Poisson distribution requires that the mean and variance of the number of failures be equal. This article suggests several alternative models that may be used for samples in which the variance exceeds the mean. First, the mean of the Poisson distribution may itself be randomly distributed across the observational units according to a gamma distribution. If so, the number of failures will have a negative binomial distribution. Second, the mean of the Poisson distribution may depend systematically upon a set of observable explanatory variables. In this case, the Poisson regression model is appropriate. Finally, the mean of the Poisson distribution may contain both a systematic component that depends upon observable variables and a random component. This situation yields a generalized Poisson regression model.     

The logistic–exponential survival distribution

For various parameter combinations, the logistic–exponential survival distribution belongs to four common classes of survival distributions: increasing failure rate, decreasing failure rate, bathtub‐shaped failure rate, and upside‐down bathtub‐shaped failure rate. Graphical comparison of this new distribution with other common survival distributions is seen in a plot of the skewness versus the coefficient of variation. The distribution can be used as a survival model or as a device to determine the distribution class from which a particular data set is drawn. As the three‐parameter version is less mathematically tractable, our major results concern the two‐parameter version. Boundaries for the maximum likelihood estimators of the parameters are derived in this article. Also, a fixed‐point method to find the maximum likelihood estimators for complete and censored data sets has been developed. The two‐parameter and the three‐parameter versions of the logistic–exponential distribution are applied to two real‐life data sets. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

Analysis and optimal design of discrete order picking technologies along a line

Order picking accounts for most of the operating expense of a typical distribution center, and thus is often considered the most critical function of a supply chain. In discrete order picking a single worker walks to pick all the items necessary to fulfill a single customer order. Discrete order picking is common not only because of its simplicity and reliability, but also because of its ability to pick orders quickly upon receipt, and thus is commonly used by e‐commerce operations. There are two primary ways to reduce the cost (walking distance required) of the order picking system. First is through the use of technology—conveyor systems and/or the ability to transmit order information to pickers via mobile units. Second is through the design—where best to locate depots (where workers receive pick lists and deposit completed orders) and how best to lay out the product. We build a stochastic model to compare three configurations of different technology requirements: single‐depot, dual‐depot, and no‐depot. For each configuration we explore the optimal design. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

Replacing nonidentical vital components to extend system life

We consider a system that depends on a single vital component. If this component fails, the system life will terminate. If the component is replaced before its failure then the system life may be extended; however, there are only a finite number of spare components. In addition, the lifetimes of these spare components are not necessarily identically distributed. We propose a model for scheduling component replacements so as to maximize the expected system survival. We find the counterintuitive result that when comparing components' general lifetime distributions based on stochastic orderings, not even the strongest ordering provides an a priori guarantee of the optimal sequencing of components. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

协议测试中测试序列生成方法综述

文章在介绍协议一致性测试基本概念的基础上,重点列举了测试序列的几种生成方法。对目前广泛采用的形式化描述模型,重点介绍其中基于有限状态机模型的测试序列生成方法,同时对基于扩展有限状态机以及确定有限状态机的测试序列生成方法也进行了介绍。文章对每一种方法介绍了其原理并分析了其使用中的局限。文章最后指出了在协议测试中面临的问题和进一步研究的方向。     

基于高阶累积量与神经网络的干扰识别算法

研究了一种基于高阶累积量和神经网络的干扰识别算法。该方法把卫星通信中常见的各种干扰信号的归一化高阶累积量作为分类特征参数,应用神经网络对特征参数进行分类训练,将接收干扰信号的归一化高阶累积量输入已训练的神经网络进行干扰类型的识别。试验结果表明:该算法在低干信比的情况下具有较高的识别准确率。