A note on the calculation of expected time-weighted backorders over a given interval

Two formulae are presented for calculating expected time-weighted backorders over a fixed time interval. One formula is a more precise form of a result found in the literature and is found using a direct intuitive approach. The second formula is derived using the steady. State distribution of inventory and is directly compatible with the use of steady-state (R, Q) models. The two formulae are compared and reconciled.     

三种坦克变速箱润滑油的试验研究

按GB/T12583—90标准,对三种坦克变速箱润滑油（50号机油,80号坦克齿轮油和18号双曲线齿轮油）进行实验室和实车评定。选择变速箱四档主动齿轮齿厚最大磨损部位磨损速率作为评定润滑油润滑效果优劣的判据:通过三台59式坦克近300摩托小时的实车试验,测定了分别采用三种润滑油的齿厚磨损速率,得出了18号双曲线齿轮油的使用性能最好,80号坦克齿轮油次之,50号润滑油最差的结论,为部队合理使用坦克变速箱润滑油提供了依据。     

Measuring the Impact of Military Spending: How Far Does a DSGE Model Deviate from Reality?

Dunne, Smith, and Willenbockel (2005) argue that the mainstream growth literature has not found military spending to be a significant determinant of economic growth, yet much of the defense economics literature has noted significant effects. This paper revisits this issue by using a DSGE-VAR approach, combining both theoretical and empirical methods. We present that the DSGE approach (estimated with the Bayesian technique) and the Bayesian VAR with the Minnesota Prior both lead to worse in-sample fit than our proposed DSGE-VAR framework. The DSGE-VAR approach reveals that a positive military spending shock boosts the U.S. economy, increasing per capita real GDP growth, consumption, inflation and interest rate. Our results are robust to alternative model specifications. Future investigations such as exploring an optimal military spending policy could adopt the approach in this paper to determine the best model – empirical, theoretical, or a combination of the two.     

A two‐echelon inventory‐location problem with service considerations

We study the problem of designing a two‐echelon spare parts inventory system consisting of a central plant and a number of service centers each serving a set of customers with stochastic demand. Processing and storage capacities at both levels of facilities are limited. The manufacturing process is modeled as a queuing system at the plant. The goal is to optimize the base‐stock levels at both echelons, the location of service centers, and the allocation of customers to centers simultaneously, subject to service constraints. A mixed integer nonlinear programming model (MINLP) is formulated to minimize the total expected cost of the system. The problem is NP‐hard and a Lagrangian heuristic is proposed. We present computational results and discuss the trade‐off between cost and service. © 2009 Wiley Periodicals, Inc. Naval Research Logistics 2009