Production planning with resources subject to congestion

A fundamental difficulty in developing effective production planning models has been accurately reflecting the nonlinear dependency between workload and lead times. We develop a mathematical programming model for production planning in multiproduct, single stage systems that captures the nonlinear dependency between workload and lead times. We then use outer linearization of this nonlinear model to obtain a linear programming formulation and extend it to multistage systems. Extensive computational experiments validate the approach and compare its results to conventional models that assume workload‐independent planning lead times. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009     

无人机电子干扰条件下的路径规划

针对机载预警雷达结合地面雷达对低空突防无人机构成的严重威胁,提出一种基于A*算法的路径规划算法.该算法分析了电子干扰和无人机RCS对雷达探测空间的影响,建立了新的雷达探测空间模型和威胁模型进行路径规划,将A*算法应用于无人机的路径规划过程.在此基础上给出了应用该方法的具体步骤,并进行了MATLAB仿真.仿真结果表明:考虑电子干扰对雷达威胁区域影响的情况下规划的飞行路径飞行器能有效回避威胁,有效提高无人机的低空突防能力.     

基于共词分析的国内语言规划与政策研究现状分析

本文以中国学术期刊网收录的1637篇文献记录为分析对象,利用聚类分析、战略坐标分析和社会网络分析等方法,对国内语言规划与政策领域的主要研究方向、发展状态和核心作者群进行分析。研究结果表明,国内语言规划与政策研究主要涉及八个方向:少数民族语言研究、官方语言研究、语言态度研究、推广普通话研究、方言研究、外语研究、语言问题研究、语言文字规范研究。其中,少数民族语言研究、官方语言研究和方言研究处于领域核心且发展比较成熟。推广普通话研究也是领域关注的核心问题,但目前发展尚不成熟。相比之下,语言态度研究、外语研究、语言文字规范研究和语言问题研究相对处于领域边缘且尚不够成熟。围绕各个研究方向均已形成了较稳定的杰出作者群体,多数学者都反映出"多主题跟进、单主题深入"的研究模式。     

空天防御作战规划问题研究

从技术与作战结合的角度,系统分析空天防御作战系统和对抗特点等问题,构建了"态势组态—目标排序—目标分配—冲突动态最优预测"新型作战规划方法,提出"博弈控制理论与方法",论述了空天防御作战规划方法论。对空天防御作战规划理论研究有一定参考价值,为发展空天防御作战规划系统提供了研究思路和技术支撑。     

Improvise,adapt and fail to overcome? Capacity building,culture and exogenous change in Sierra Leone

Military capacity building (MCB) is as problematic as it is ubiquitous, with the British experience in Sierra Leone providing a rare example of ostensible success. This article critiques the dominant conceptualisation of MCB as purely a principal–agent (PA) problem, using military change scholarship to examine the impact of wartime British intervention on the Sierra Leonean armed forces. Here, indigenous military change was both externally driven and fundamentally adaptive in nature, allowing MCB to bypass some of the difficulties predicted by PA models. However, this adaptive approach nonetheless failed to reconcile Western military values with prevailing Sierra Leonean culture, complicating post-war stabilisation efforts.     

Spaghetti: systems thinking and the US Army

In the mid-2000s, the United States Army was embroiled in counterinsurgency missions in Iraq and Afghanistan that required deeper understanding of local social systems. The Army turned to systems thinking and design thinking to model and understand the world, define problems, and develop approaches to strategic and operational challenges. However, the Army’s approach as expressed in publications and doctrine encourages the development of complicated, unsupported, and unfalsifiable hypotheses. The risk is that the Army will act on incorrect assumptions and develop plans that are fragile.     

More military base closure? Considering the alternatives*

Despite multiple base closing rounds, the United States Department of Defense still has excess base capacity, and thus President Trump and high-level Defense Department officials are calling for more base closure through the Base Realignment and Closure (BRAC) process. However, another BRAC may not be the optimal solution, because simple base closure is not an efficient way to reduce surplus base capacity. Thus, Defense Department officials should consider other methods to reduce surplus capacity, including reduction in base size, leasing excess base property, or transferring it to another government agency for a variety of alternative uses. The surplus capacity issue also offers an opportunity to DOD to reassess base utilization, to update base requirements with current and future force structure. While BRAC focuses on American military bases, the process and alternatives also have international applications.     

Implementing defence policy: a benchmark-“lite”

Most countries put significant amounts of time and effort in writing and issuing high-level policy documents. These are supposed to guide subsequent national defence efforts. But do they? And how do countries even try to ensure that they do? This paper reports on a benchmarking effort of how a few “best of breed” small- to medium-sized defence organisations (Australia, Canada, and New Zealand) deal with these issues. We find that most countries fail to link goals to resources and pay limited attention to specific and rigorous ex-ante or post-hoc evaluation, even when compared to their own national government-wide provisions. We do, however, observe a (modest) trend towards putting more specific goals and metrics in these documents that can be – and in a few rare cases were – tracked. The paper identifies 42 concrete policy “nuggets” – both “do’s and don’ts” – that should be of interest to most defence policy planning/analysis communities. It ends with two recommendations that are in line with recent broader (non-defence) scholarship on the policy formulation-policy implementation gap: to put more rigorous emphasis on implementation (especially on achieving desired policy effects), but to do so increasingly in more experiential (“design”) ways, rather than in industrial-age bureaucratic ones (“PPBS”-systems).     

Evergreening and operational risk under price competition

“Evergreening” is a strategy wherein an innovative pharmaceutical firm introduces an upgrade of its current product when the patent on this product expires. The upgrade is introduced with a new patent and is designed to counter competition from generic manufacturers that seek to imitate the firm's existing product. However, this process is fraught with uncertainty because the upgrade is subject to stringent guidelines and faces approval risk. Thus, an incumbent firm has to make an upfront production capacity investment without clarity on whether the upgrade will reach the market. This uncertainty may also affect the capacity investment of a competing manufacturer who introduces a generic version of the incumbent's existing product but whose market demand depends on the success or failure of the upgrade. We analyze a game where capacity investment occurs before uncertainty resolution and firms compete on prices thereafter. Capacity considerations that arise due to demand uncertainty introduce new factors into the evergreening decision. Equilibrium analysis reveals that the upgrade's estimated approval probability needs to exceed a threshold for the incumbent to invest in evergreening. This threshold for evergreening increases as the intensity of competition in the generic market increases. If evergreening is optimal, the incumbent's capacity investment is either decreasing or nonmonotonic with respect to low end market competition depending on whether the level of product improvement in the upgrade is low or high. If the entrant faces a capacity constraint, then the probability threshold for evergreening is higher than the case where the entrant is not capacity constrained. Finally, by incorporating the risk‐return trade‐off that the incumbent faces in terms of the level of product improvement versus the upgrade success probability, we can characterize policy for a regulator. We show that the introduction of capacity considerations may maximize market coverage and/or social surplus at incremental levels of product improvement in the upgrade. This is contrary to the prevalent view of regulators who seek to curtail evergreening involving incremental product improvement. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 71–89, 2016     

Level workforce planning for multistage transfer lines

In this article, we define two different workforce leveling objectives for serial transfer lines. Each job is to be processed on each transfer station for c time periods (e.g., hours). We assume that the number of workers needed to complete each operation of a job in precisely c periods is given. Jobs transfer forward synchronously after every production cycle (i.e., c periods). We study two leveling objectives: maximin workforce size () and min range (R). Leveling objectives produce schedules where the cumulative number of workers needed in all stations of a transfer line does not experience dramatic changes from one production cycle to the next. For and a two‐station system, we develop a fast polynomial algorithm. The range problem is known to be NP‐complete. For the two‐station system, we develop a very fast optimal algorithm that uses a tight lower bound and an efficient procedure for finding complementary Hamiltonian cycles in bipartite graphs. Via a computational experiment, we demonstrate that range schedules are superior because not only do they limit the workforce fluctuations from one production cycle to the next, but they also do so with a minor increase in the total workforce size. We extend our results to the m‐station system and develop heuristic algorithms. We find that these heuristics work poorly for min range (R), which indicates that special structural properties of the m‐station problem need to be identified before we can develop efficient algorithms. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 577–590, 2016