Making defense planning meaningful: the evolution of strategic guidance in the Hungarian Ministry of Defense

Hungary, a former communist state, adapted a Western-style defense planning system during the 1990s and 2000s. Although on the surface the elements of this planning system were similar to the planning programming budgeting system (PPBS) developed by the US Department of Defense, strategic guidance for defense planning has not been properly developed until recently. Thus, albeit PPBS-based defense plans were developed in the Hungarian Ministry of Defense (Hungarian MoD) regularly, they lacked both an expression of clear priorities and strategic focus. This article delineates the evolution of strategic guidance in the Hungarian MoD concentrating on current developments, and introduces the newly elaborated analytical concepts and tools, which helped to create needed strategic guidance in Hungary.     

Expansion planning for waste‐to‐energy systems using waste forecast prediction sets

We consider an expansion planning problem for Waste‐to‐Energy (WtE) systems facing uncertainty in future waste supplies. The WtE expansion plans are regarded as strategic, long term decisions, while the waste distribution and treatment are medium to short term operational decisions which can adapt to the actual waste collected. We propose a prediction set uncertainty model which integrates a set of waste generation forecasts and is constructed based on user‐specified levels of forecasting errors. Next, we use the prediction sets for WtE expansion scenario analysis. More specifically, for a given WtE expansion plan, the guaranteed net present value (NPV) is evaluated by computing an extreme value forecast trajectory of future waste generation from the prediction set that minimizes the maximum NPV of the WtE project. This problem is essentially a multiple stage min‐max dynamic optimization problem. By exploiting the structure of the WtE problem, we show this is equivalent to a simpler min‐max optimization problem, which can be further transformed into a single mixed‐integer linear program. Furthermore, we extend the model to optimize the guaranteed NPV by searching over the set of all feasible expansion scenarios, and show that this can be solved by an exact cutting plane approach. We also propose a heuristic based on a constant proportion distribution rule for the WtE expansion optimization model, which reduces the problem into a moderate size mixed‐integer program. Finally, our computational studies demonstrate that our proposed expansion model solutions are very stable and competitive in performance compared to scenario tree approaches. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 47–70, 2016     

The contexts of strategy as a guide for defense planning in the Philippines

Efforts toward developing an independent and credible Philippine defense policy were revived when Benigno Simeon C. Aquino III was elected President of the Philippines in 2010. President Aquino renewed the military modernization program in 2012 and emphasized the necessity of a “minimum credible defense posture.” Given the modernization efforts of the government, this article aims to contribute to the development of the concept of minimum credible defense posture by exploring how theory contributes to defense planning. It argues that the contexts of strategy are useful in planning for national defense because these contexts can provide a conceptual framework for defense planners. It proceeds in three parts: the opening section reviews the literature on defense planning; the second surveys the context of developing strategies as discussed in the General Theory of Strategy; and the last provides a definition of minimum credible defense and applies the context of developing strategies to the case of the Philippines.     

基于IAFSA的四自由度翼伞分段归航设计

为实现翼伞系统的精确空投,需要对其归航轨迹作合理规划。根据翼伞系统自身的运动特性及操纵特性,采用分段归航策略。在四自由度翼伞模型下,利用各轨迹段的几何关系,建立表征轨迹优劣程度的目标函数。基于改进的人工鱼群算法,对目标函数进行参数寻优,进而得到轨迹的设计参数。仿真结果表明,所提出的改进方法能加快算法的收敛速度,所规划的轨迹满足了精确落点和逆风着陆的要求。     

基于黑板模型的分布式协同任务决策方法研究

基于黑板模型的分布式指挥控制网络为未来复杂环境下海战中多平台间的高效协同提供了新思路,通过构建应用于多航母群联合海战的分布式协同网络,对多航母群联合海战下的系统负载进行了研究,建立了一种多平台任务决策的数学模型,采用嵌套遗传算法进行了仿真求解,得到了理想的任务决策方案。最后对由于目标函数中内部负载权重系数不同取值所引起的不同任务决策结果进行了比较,验证了将基于黑板模型的分布式协同网络应用于多航母海战协同决策的科学性,为分布式海战协同决策网络的后续研究工作奠定了基础。     

Modeling multiple stage manufacturing systems with generalized costs and capacity issues

This study introduces one modeling methodology that describes a broad range of multiple stage production planning issues, including multiple limited resources with setup times and joint fixed cost relationships. An existing production system is modeled in this fashion, creating a new set of 1350 highly generalized benchmark problems. A computational study is conducted with the 1350 benchmark problems introduced in this paper and 2100 benchmark problems, with more restrictive assumptions, from the existing literature. The relative merits of a decomposition‐based algorithm and a neighborhood search technique known as NIPPA, or the Non‐sequential Incremental Part Period Algorithm, are assessed. NIPPA is generally the more successful of the two techniques, although there are specific instances in which the decomposition‐based algorithm displayed a distinct advantage. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005     

Robust capacity planning in semiconductor manufacturing

We present a stochastic programming approach to capacity planning under demand uncertainty in semiconductor manufacturing. Given multiple demand scenarios together with associated probabilities, our aim is to identify a set of tools that is a good compromise for all these scenarios. More precisely, we formulate a mixed‐integer program in which expected value of the unmet demand is minimized subject to capacity and budget constraints. This is a difficult two‐stage stochastic mixed‐integer program which cannot be solved to optimality in a reasonable amount of time. We instead propose a heuristic that can produce near‐optimal solutions. Our heuristic strengthens the linear programming relaxation of the formulation with cutting planes and performs limited enumeration. Analyses of the results in some real‐life situations are also presented. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.     

The failure of defense planning in European Post-Communist Defense Institutions: ascertaining causation and determining solutions

By any objective measure, defense institutions in Central and Eastern Europe have all but universally been incapable of producing viable defense plans that are based on objective costing and operational planning data. This situation exists in spite the provision of considerable Western advice and assistance, let alone reporting to and receiving assessments by NATO’s International Staff under Partnership for Peace, as well as via the integrated defense planning and reporting systems. An explanation for this systematic failure across European post-Communist defense institutions can be found in the continued slow development of an over-arching policy framework which directs and approves all activities of the armed forces, as well as the de-centralization of financial decision-making down to capability providers. The essay ends with an examination of the adverse effects of the early introduction of planning programming, budgeting system (PPBS), have had on the development of effective policy and planning capabilities within these defense institutions.     

自动化电弧喷涂路径偏移间距的优化模型

基于电弧喷涂沉积丘的轮廓呈高斯分布的假设,并结合实验结果,建立了电弧喷涂沉积丘轮廓的数学模型,由此推导出了自动化喷涂过程中平行路径偏移间距这一重要参量的优化模型。该模型为合理规划自动化喷涂的路径提供了依据。     

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