The value of information sharing in a two‐stage supply chain with production capacity constraints

We consider a simple two‐stage supply chain with a single retailer facing i.i.d. demand and a single manufacturer with finite production capacity. We analyze the value of information sharing between the retailer and the manufacturer over a finite time horizon. In our model, the manufacturer receives demand information from the retailer even during time periods in which the retailer does not order. To analyze the impact of information sharing, we consider the following three strategies: (1) the retailer does not share demand information with the manufacturer; (2) the retailer does share demand information with the manufacturer and the manufacturer uses the optimal policy to schedule production; (3) the retailer shares demand information with the manufacturer and the manufacturer uses a greedy policy to schedule production. These strategies allow us to study the impact of information sharing on the manufacturer as a function of the production capacity, and the frequency and timing in which demand information is shared. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

白炽灯对棉质材料的引燃性能研究

通过对不同功率白炽灯引燃100％棉质材料的研究,分析了白炽灯引燃棉质材料引发火灾的危险性。利用半导体点温计分别对不同功率白炽灯表面及棉布的温度进行记录,根据温度随时间的变化情况、可燃物被引燃情况,分析了不同功率白炽灯对棉布的引燃性能。     

基于科学发展观视角下的会计教学改革

随着高等教育的大众化,社会对会计人才需求呈现出多层次的特点,现代会计教育已进入素质教育的新阶段。注重学生创造性思维的培养,注重学生能力与素质的提高应成为各高校今后会计教学改革的方向。本文从科学发展观的视角,在分析了会计本科教学现状的基础上,理性地提出了要实现会计教学培养目标,必须转变教育观念,适应科学发展观的要求,推动会计教学改革。     

战术数据链网络设计优化方法

网络设计优化问题直接关系到战术数据链系统效能的发挥。在分析数据链系统中不同消息类别有不同系统响应时间要求的基础上,提出了一种新的网络设计优化方法。通过建立模型讨论了单个数据链轮询网络的轮询周期、网络成员容量、每个轮询周期内各成员的点名次数等因素间的数学关系。并以Link-11为例进行分析计算。结果表明,该分析方法有效可行,为解决战术数据链网络设计及优化问题提供了一种思路。     

数字化部队作战能力评估指标体系构建

探讨了数字化部队作战能力评估的指导思想和原则,从现代战争系统模型分解图的指标构建思想出发,以系统科学与工程理论为指导,构建数字化部队战争系统模型分解图,将现代战争系统分解成部队与武器子系统、电子信息子系统、指挥决策子系统和综合保障子系统,并分别对各子系统的能力指标内涵进行了详细解释,用信息系统描述了各指标体系的能力构成。     

Optimal capacity in a coordinated supply chain

We consider a supply chain in which a retailer faces a stochastic demand, incurs backorder and inventory holding costs and uses a periodic review system to place orders from a manufacturer. The manufacturer must fill the entire order. The manufacturer incurs costs of overtime and undertime if the order deviates from the planned production capacity. We determine the optimal capacity for the manufacturer in case there is no coordination with the retailer as well as in case there is full coordination with the retailer. When there is no coordination the optimal capacity for the manufacturer is found by solving a newsvendor problem. When there is coordination, we present a dynamic programming formulation and establish that the optimal ordering policy for the retailer is characterized by two parameters. The optimal coordinated capacity for the manufacturer can then be obtained by solving a nonlinear programming problem. We present an efficient exact algorithm and a heuristic algorithm for computing the manufacturer's capacity. We discuss the impact of coordination on the supply chain cost as well as on the manufacturer's capacity. We also identify the situations in which coordination is most beneficial. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

Risk‐sensitive sizing of responsive facilities

We develop a risk‐sensitive strategic facility sizing model that makes use of readily obtainable data and addresses both capacity and responsiveness considerations. We focus on facilities whose original size cannot be adjusted over time and limits the total production equipment they can hold, which is added sequentially during a finite planning horizon. The model is parsimonious by design for compatibility with the nature of available data during early planning stages. We model demand via a univariate random variable with arbitrary forecast profiles for equipment expansion, and assume the supporting equipment additions are continuous and decided ex‐post. Under constant absolute risk aversion, operating profits are the closed‐form solution to a nontrivial linear program, thus characterizing the sizing decision via a single first‐order condition. This solution has several desired features, including the optimal facility size being eventually decreasing in forecast uncertainty and decreasing in risk aversion, as well as being generally robust to demand forecast uncertainty and cost errors. We provide structural results and show that ignoring risk considerations can lead to poor facility sizing decisions that deteriorate with increased forecast uncertainty. Existing models ignore risk considerations and assume the facility size can be adjusted over time, effectively shortening the planning horizon. Our main contribution is in addressing the problem that arises when that assumption is relaxed and, as a result, risk sensitivity and the challenges introduced by longer planning horizons and higher uncertainty must be considered. Finally, we derive accurate spreadsheet‐implementable approximations to the optimal solution, which make this model a practical capacity planning tool.© 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

Strategic capacity decision‐making in a stochastic manufacturing environment using real‐time approximate dynamic programming

In this study, we illustrate a real‐time approximate dynamic programming (RTADP) method for solving multistage capacity decision problems in a stochastic manufacturing environment, by using an exemplary three‐stage manufacturing system with recycle. The system is a moderate size queuing network, which experiences stochastic variations in demand and product yield. The dynamic capacity decision problem is formulated as a Markov decision process (MDP). The proposed RTADP method starts with a set of heuristics and learns a superior quality solution by interacting with the stochastic system via simulation. The curse‐of‐dimensionality associated with DP methods is alleviated by the adoption of several notions including “evolving set of relevant states,” for which the value function table is built and updated, “adaptive action set” for keeping track of attractive action candidates, and “nonparametric k nearest neighbor averager” for value function approximation. The performance of the learned solution is evaluated against (1) an “ideal” solution derived using a mixed integer programming (MIP) formulation, which assumes full knowledge of future realized values of the stochastic variables (2) a myopic heuristic solution, and (3) a sample path based rolling horizon MIP solution. The policy learned through the RTADP method turned out to be superior to polices of 2 and 3. © 2010 Wiley Periodicals, Inc. Naval Research Logistics 2010     

The Demand for Military Expenditure in Europe: The Role of Fiscal Space in the Context of a Resurgent Russia

A variant of established work on the demand for military expenditure is developed based on a practical concept of fiscal space from the perspective of short-term government choices concerning public expenditures. A new indicator, referred to as fiscal capacity, is defined and used as a candidate explanatory variable in an empirical model of European defence spending over the 2007–2016 period. Fiscal capacity is found to outperform simpler measurements of economic conditions, notably GDP growth forecasts, in explaining changes in defence spending efforts as a share of GDP. Regarding security environment variables, the results suggest that Russia has recently come to be seen as a potential military threat by European nations, leading to defence spending increases, the more so the shorter the distance to stationed or deployed Russian forces, and particularly so by those European nations that have a land border with Russia. A prospective exercise is then carried out in order to assess the capacity of EU member states that are also members of NATO to reach NATO’s 2% goal for defence spending over a mid-term horizon.     

Excess procurement strategies by a dominant buyer under constrained supply

Supply chains are often characterized by the presence of a dominant buyer purchasing from a supplier with limited capacity. We study such a situation where a single supplier sells capacity to an established and more powerful buyer and also to a relatively less powerful buyer. The more powerful buyer enjoys the first right to book her capacity requirements at supplier's end, and then the common supplier fulfills the requirement of the less powerful buyer. We find that when the supplier's capacity is either too low (below the lower threshold) or too high (above the higher threshold), there is no excess procurement as compared to the case when supplier has infinite capacity. When the supplier's capacity is between these two thresholds, the more powerful buyer purchases an excess amount in comparison to the infinite capacity case.