The Hungarian experience with Gripen fighter aircraft

The post-communist countries transition from the Warsaw Pact style of platforms and systems to Western-compatible capabilities has never been an easy task or a process without conflicts. This was no different for the Visegrád countries either, in which case the Hungarian Gripen procurement stands out. After much debate, Budapest decided to modernize its fighter fleet with the not battle tested Swedish-made Gripen fighter aircraft. This decision received several critiques due to the lack of transparency in the selection process and the initial lack of NATO-required systems. Subsequently, the fleet has had to operate in a financially demanding environment. Moreover, the air force has lost two aircrafts in accidents. Now that the jets are in the middle of their envisaged life cycle, it is more than appropriate to answer the question if the Gripens can utilize their full combat potential or will they fail the test of time?     

美国网络空间作战能力建设

网络空间越来越被世界各国公认为是继陆地、海洋、空中和太空之后的第五个作战域,为获得和保持像其它作战域那样世界领先的军事优势,美国正在大力进行网络空间作战能力建设。提出了美国网络空间作战能力建设框架,从战略规划、作战力量、作战理论、作战训练、武器装备、战场基础环境、人才培养和作战联盟八个方面全面总结了美国近年来在网络空间作战能力建设方面的主要做法。     

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。     

Balancing a one‐way corridor capacity and safety‐oriented reliability: A stochastic optimization approach for metro train timetabling

In urban rail transit systems of large cities, the headway and following distance of successive trains have been compressed as much as possible to enhance the corridor capacity to satisfy extremely high passenger demand during peak hours. To prevent train collisions and ensure the safety of trains, a safe following distance of trains must be maintained. However, this requirement is subject to a series of complex factors, such as the uncertain train braking performance, train communication delay, and driver reaction time. In this paper, we propose a unified mathematical framework to analyze the safety‐oriented reliability of metro train timetables with different corridor capacities, that is, the train traffic density, and determine the most reliable train timetable for metro lines in an uncertain environment. By employing a space‐time network representation in the formulations, the reliability‐based train timetabling problem is formulated as a nonlinear stochastic programming model, in which we use 0‐1 variables to denote the time‐dependent velocity and position of all involved trains. Several reformulation techniques are developed to obtain an equivalent mixed integer programming model with quadratic constraints (MIQCP) that can be solved to optimality by some commercial solvers. To improve the computational efficiency of the MIQCP model, we develop a dual decomposition solution framework that decomposes the primal problem into several sets of subproblems by dualizing the coupling constraints across different samples. An exact dynamic programming combined with search space reduction strategies is also developed to solve the exact optimal solutions of these subproblems. Two sets of numerical experiments, which involve a relatively small‐scale case and a real‐world instance based on the operation data of the Beijing subway Changping Line are implemented to verify the effectiveness of the proposed approaches.     

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.     

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).     

Precision cyber weapon systems: An important component of a responsible national security strategy?

Given the advances made in conventional weapon capabilities, precision should by now be the accepted and expected norm in cyberspace as well. In this article I argue that developing precision cyber weapon systems, to be used during a lawful conflict, can be an important part of a responsible national security strategy to reduce the amount of violence and physical destruction in conflicts. I first describe a precision cyber weapon system in a military context. I then present three compelling rationales for the development of precision cyber weapon systems based on ethical, operational, and financial considerations. To support the position, I address several arguments that have been levied against their development. Thereafter I present several recommendations for a way ahead.     

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     

Capacity expansion and cost efficiency improvement in the warehouse problem

The warehouse problem with deterministic production cost, selling prices, and demand was introduced in the 1950s and there is a renewed interest recently due to its applications in energy storage and arbitrage. In this paper, we consider two extensions of the warehouse problem and develop efficient computational algorithms for finding their optimal solutions. First, we consider a model where the firm can invest in capacity expansion projects for the warehouse while simultaneously making production and sales decisions in each period. We show that this problem can be solved with a computational complexity that is linear in the product of the length of the planning horizon and the number of capacity expansion projects. We then consider a problem in which the firm can invest to improve production cost efficiency while simultaneously making production and sales decisions in each period. The resulting optimization problem is non‐convex with integer decision variables. We show that, under some mild conditions on the cost data, the problem can be solved in linear computational time. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 367–373, 2016