Operating Costs of Aging Air Force Aircraft: Adjusting for Aggregate Budget Effects

The rate at which operating costs grow as aircraft age is important for setting operating budgets and for deciding when to replace aging systems. While studies using data from the 1990's typically found 1–3 percent real rates of growth in operating costs as aircraft age, studies using data from the 2000's found greater rates, for example in the 4–6 percent range. Growth in the total U.S. Air Force budget during the 2000s appears to explain much of the higher estimated annual growth rates in operating costs per flying hour beyond the growth rate intrinsic to the aging of the fleet.     

航空随队支援干扰掩护区仿真建模研究

干扰暴露区及干扰扇面等传统评估指标对静态干扰部署可以进行有效评估分析,对机动干扰掩护难以进行准确描述分析。为有效评估电子对抗航空兵随队支援干扰能力,以及准确进行航空兵突防编队配置及干扰力量需求分析,引入了干扰掩护区的概念,并建立相关模型进行仿真计算,得出3条电子对抗随队支援航空兵突防的运用启示。     

高功率微波弹的杀伤效果分析与仿真

根据高功率微波弹微波脉冲的攻击入射角,给出了高功率微波弹杀伤区域模型,结合高功率微波损坏和干扰电子元器件的能量阈值,提出了高功率微波弹对目标的失效区、干扰区及安全区的概念,并建立相应的数学模型进行了仿真分析,为高功率微波弹攻击参数的设定及实际的作战运用提供了理论依据。     

Military expenditure and economic growth in Middle Eastern countries and Turkey: a non-linear panel data approach

The economic growth effects of military expenditure have been the subject of a large literature in defence economics. Theories on the economic impacts of military expenditure greatly differ and include arguments that they either enhance economic growth or crowd out productive investments. Empirical literature on defence expenditure and economic growth nexus generally employs linear specifications to investigate the impact of defence expenditures on economic growth. Although it is now well established that many economic variables may have a non-linear data-generating mechanism, it seems that this reality has long been neglected in empirical work on defence–growth nexus. This paper attempts to fill this gap by employing non-linear panel data models to examine the effects of military expenditures on economic growth for Middle Eastern countries and Turkey, for the time period 1988–2012. Results show that the effect of military expenditure on economic growth is nonlinear such that the state of the economy actually determines the effect of the former on the latter. This is important not only in showing asymmetric relationship between these variables but also in revealing the reasons of mixed results of earlier literature.     

以可靠性为中心的维修及其模型支持

从RCM分析的基本过程入手,分析了进行RCM决策模型研究的必要性,简要介绍了RCM分析决策过程,探讨了RCM决策模型的分类方法,提出了RCM建模研究的基本设想。     

DTM在坦克视景仿真中的应用

介绍了DTM的结构、数据处理.针对坦克射击模拟器的要求,利用DTM,建立一套三维地形.以微机图形工作站为主要开发平台,建立在真实地为基础上的视景模拟逼真度得以提高.     

An approximate dynamic programing approach to the development of heuristics for the scheduling of impatient jobs in a clearing system

A single server is faced with a collection of jobs of varying duration and urgency. Each job has a random lifetime during which it is available for nonpreemptive service. Should a job's lifetime expire before its service begins then it is lost from the system unserved. The goal is to schedule the jobs for service to maximize the expected number served to completion. Two heuristics have been proposed in the literature. One (labeled π^S) operates a static priority among the job classes and works well in a “no premature job loss” limit, whereas the second (π^M) is a myopic heuristic which works well when lifetimes are short. Both can exhibit poor performance for problems at some distance from the regimes for which they were designed. We develop a robustly good heuristic by an approximative approach to the application of a policy improvement step to the asymptotically optimal heuristic π^S, in which we use a fluid model to obtain an approximation for the value function of π^S. The performance of the proposed heuristic is investigated in an extensive numerical study. © 2010 Wiley Periodicals, Inc. Naval Research Logistics 2010     

多阶段任务系统任务持续能力数学评价模型研究

分析了多阶段任务系统(PMS)及任务可靠度、可信度和任务效能等任务持续能力评价参数。结合实际装备系统大部分属于可用马尔可夫过程进行描述的可修复系统的特点,为简化模型复杂程度提出了一些合理的假设条件。针对两状态PMS,通过分析其状态转移关系,从阶段任务成功概率和阶段任务间转换概率的概念出发,分析给出其计算方法。结合对可信度和任务效能等参数的分析结果,建立其计算模型,从而建立了多阶段任务系统任务持续能力数学评价模型。最后结合常见的“靶场打靶”任务,通过对比仿真结果进行了模型的实例验证。     

Inventory control and periodic price discounting campaigns

This paper develops an inventory model that determines replenishment strategies for buyers facing situations in which sellers offer price‐discounting campaigns at random times as a way to drive sales or clear excess inventory. Specifically, the model deals with the inventory of a single item that is maintained to meet a constant demand over time. The item can be purchased at two different prices denoted high and low. We assume that the low price goes into effect at random points in time following an exponential distribution and lasts for a random length of time following another exponential distribution. We highlight a replenishment strategy that will lead to the lowest inventory holding and ordering costs possible. This strategy is to replenish inventory only when current levels are below a certain threshold when the low price is offered and the replenishment is to a higher order‐up‐to level than the one currently in use when inventory depletes to zero and the price is high. Our analysis provides new insight into the behavior of the optimal replenishment strategy in response to changes in the ratio of purchase prices together with changes in the ratio of the duration of a low‐price period to that of a high‐price period. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007.     

Bayesian strategies for dynamic pricing in e‐commerce

E‐commerce platforms afford retailers unprecedented visibility into customer purchase behavior and provide an environment in which prices can be updated quickly and cheaply in response to changing market conditions. This study investigates dynamic pricing strategies for maximizing revenue in an Internet retail channel by actively learning customers' demand response to price. A general methodology is proposed for dynamically pricing information goods, as well as other nonperishable products for which inventory levels are not an essential consideration in pricing. A Bayesian model of demand uncertainty involving the Dirichlet distribution or a mixture of such distributions as a prior captures a wide range of beliefs about customer demand. We provide both analytic formulas and efficient approximation methods for updating these prior distributions after sales data have been observed. We then investigate several strategies for sequential pricing based on index functions that consider both the potential revenue and the information value of selecting prices. These strategies require a manageable amount of computation, are robust to many types of prior misspecification, and yield high revenues compared to static pricing and passive learning approaches. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007