Bayesian inference for a Lanchester type combat model

We undertake inference for a stochastic form of the Lanchester combat model. In particular, given battle data, we assess the type of battle that occurred and whether or not it makes any difference to the number of casualties if an army is attacking or defending. Our approach is Bayesian and we use modern computational techniques to fit the model. We illustrate our method using data from the Ardennes campaign. We compare our results with previous analyses of these data by Bracken and Fricker. Our conclusions are somewhat different to those of Bracken. Where he suggests that a linear law is appropriate, we show that the logarithmic or linear‐logarithmic laws fit better. We note however that the basic Lanchester modeling assumptions do not hold for the Ardennes data. Using Fricker's modified data, we show that although his “super‐logarithmic” law fits best, the linear, linear‐logarithmic, and logarithmic laws cannot be ruled out. We suggest that Bayesian methods can be used to make inference for battles in progress. We point out a number of advantages: Prior information from experts or previous battles can be incorporated; predictions of future casualties are easily made; more complex models can be analysed using stochastic simulation techniques. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 541–558, 2000     

Requirements of an “optimizer” for computer simulations

Computer simulation has many advantages. However, one major disadvantage is that, in all too many cases, the attempt to use computer simulation to find an optimum solution to a problem rapidly degenerates into a trial-and-error process. Techniques for overcoming this disadvantage, i. e., for making optimization and computer simulation more compatible, are applicable at two points in the development of the overall computer simulation. Techniques which are used within actual construction of the mathematical models comprising the simulation will be labeled as internal methods, while those which are used after the simulation has been completely developed will be termed external methods Because external methods appear to offer the largest potential payoff, discussion is restricted to these methods, which are essentially search techniques. In addition, the development of an “Optimizer” computer program based on these techniques is suggested Although drawbacks to the use of search techniques in the computer simulation framework exist, these techniques do offer potential for “optimization.” The modification of these techniques to satisfy the requirements of an “Optimizer” is discussed.     

基于ARIS的战时修理业务流程仿真研究

利用ARIS建模方法与工具，对战时装备修理业务流程进行了仿真研究。以陆军某机步师某型装备为例，给出了战时修理业务的主流程模型以及各分支模型，通过仿真运行及结果分析，得出了制约该流程的瓶颈和需要进一步优化的对象，为装备维修保障过程仿真提供了一个很好的思路和方法。该方法对于开发战时维修保障效能仿真评估系统，实现维修保障系统的动态仿真和全要素评估具有重要的支撑作用。     

Advancing “Defence-in-depth”: intelligence and systems dynamics

This article aims to encourage the fostering of more systems thinking, and its greater exploitation, within the domain of contemporary intelligence. With particular focus on “micro systems thinking” and with reference to key intelligence processes, such as intelligence analysis, the utility of many systems dynamics within the intelligence context seeks to be further revealed. Through their greater collective harnessing, including up to “System of Systems” (“SoS”) dynamics, and promoting all that they can offer, more sophisticated overarching operational-to-strategic/policy “ends,” notably that of “defence-in-depth,” can be viably further advanced in a sustainable manner into the future. Arguably, a much-needed transformative impact on contemporary intelligence can also be increasingly realised through comprehensively engaging in and with more systems and SoS thinking. Aiding civil protection tasks, crisis management, emergency planners, and civil contingency practitioners likewise gain.     

THE NPT

This article assesses the successes and failures of the Treaty on the Non-Proliferation of Nuclear Weapons (NPT) since its creation in 1968 by developing and applying a set of “metrics” to each of the NPT's substantive articles as well as to its withdrawal provisions. In light of this analysis, the article also puts forward some specific proposals for strengthening the NPT and its implementation, with a view to the debate and decisions at the upcoming 2010 NPT Review Conference. A concluding section turns explicitly to the 2010 NPT Review Conference and proposes pursuit of agreement on three NPT Action Plans: one for nonproliferation, one for peaceful uses, and one for nuclear disarmament. Combining vision and practicable steps, these Action Plans would set out a roadmap for action between the 2010 and the 2015 NPT Review Conferences. They could provide a foundation for substantive exchanges—in this case, on progress toward their implementation—during the preparations for the 2015 conference.     

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     

A continuous submarine versus submarine game

This paper analyzes, from a game-theoretic standpoint, the simultaneous choice of speeds by a transitor and by an SSK which patrols back and forth perpendicular to the transitor's course. Using idealized acoustic assumptions and a cookie-cutter detection model which ignores counterdetection, we are able to present the problem as a continuous game, and to determine an analytic solution. The results indicate that with these assumptions, there are conditions under which neither a “go fast” nor a “go slow” strategy is optimal. The game provides a good example of a continuous game with a nontrivial solution which can be solved effectively.     

COURTING THE GLOBAL SOUTH WITH “DUAL-BENEFIT” NONPROLIFERATION ENGAGEMENT

President Barack Obama and an array of other Western leaders continue to assert that the spread of weapons of mass destruction (WMD) to non-state actors is one of most pressing challenges to global security today. Yet, Western efforts to engage governments—particularly governments across the global South—in a practical nonproliferation dialogue have largely yielded disappointing results. This viewpoint examines the need for a new strategy to engage the developing world in nonproliferation programs. It argues that strategies focused strictly on WMD nonproliferation are unsustainable, and ultimately are destined for failure. An alternative “dual-benefit” nonproliferation engagement strategy utilizes the enlightened self-interest of partner governments needed to achieve broad-based buy-in among all partners. In a concluding section, we recommend that the “Group of 8” Global Partnership Against the Spread of Weapons and Materials of Mass Destruction standardize this model of nonproliferation engagement as it sets out to identify and fund WMD nonproliferation capacity-building initiatives beyond the states of the former Soviet Union.     

Concept costing for defence projects: the problem and its solution

It is intrinsic to the nature of military competition that the unit acquisition costs of defence systems rise generation by generation. Traditional “bottom‐up” methods of cost‐estimating cannot meet the increasing demands for extensive studies of many options before commencing design and, while “top‐down” estimating techniques are an improvement, in particular by reducing the time required for preparing estimates, they also are inadequate to meet current requirements. A new method has been devised, therefore, further developing “top‐down” methods using Bayesian techniques to make best use of the available information, whether certain or uncertain, and its accuracy established by example.     

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 danger of “hybrid warfare” from a sophisticated adversary: the Russian “hybridity” in the Ukrainian conflict

The term “hybrid warfare” is a new one that the West began to use to explain its failure to cope with asymmetric threats. Focusing on the war on global terrorism, the West temporarily withdrew its attention from traditional adversaries, such as Russia, which has used this gap and has audaciously returned to the stage as a global actor. Until the Russian annexation of the Crimean Peninsula in 2014 and inflaming the Ukrainian crisis, most Western authors attributed “hybrid threats” mostly to non-state actors. But the Ukrainian scenario showed the true face of “hybridity” in the modern battlefield when practised by a powerful state actor. Russian “hybrid warfare” in Ukraine has already been seen as a combination of conventional and unconventional methods, that have been complemented with other instruments of national power – diplomatic, economic and information. The purpose of this article is, through an analysis of the Ukrainian scenario, to demonstrate that although the term “hybrid” is new, the concept itself is old and is a continuation of already seen doctrine from the Cold War era. Although “hybrid threats” can come both from state and non-state actors, the Russian interference in Ukraine is proof that they are especially dangerous for the West if, or when, they are initiated from a traditional, sophisticated adversary that has the capacity to use all forms of warfare.     

An approximate planning model for distributed computing networks

We develop an approximate planning model for a distributed computing network in which a control system oversees the assignment of information flows and tasks to a pool of shared computers, and describe several optimization applications using the model. We assume that the computers are multithreaded, and have differing architectures leading to varying and inconsistent processing rates. The model is based on a discrete‐time, continuous flow model developed by Graves [Oper Res 34 (1986), 522–533] which provides the steady‐state moments of production and work‐in‐queue quantities. We make several extensions to Graves' model to represent distributed computing networks. First, we approximately model control rules that are nonlinear functions of the work‐in‐queue at multiple stations through a linearization approach. Second, we introduce an additional noise term on production and show its use in modeling the discretization of jobs. Third, we model groups of heterogeneous computers as aggregate, “virtual computing cells” that process multiple tasks simultaneously, using a judiciously selected control rule. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.     

Analysis of the stress wave and rarefaction wave produced by hypervelocity impact of sphere onto thin plate

Shock wave is emitted into the plate and sphere when a sphere hypervelocity impacts onto a thin plate. The fragmentation and phase change of the material caused by the propagation and unloading of shock wave could result in the formation of debris cloud eventually. Propagation models are deduced based on one-dimensional shock wave theory and the geometry of sphere, which uses elliptic equations (corresponding to ellipsoid equations in physical space) to describe the propagation of shock wave and the rarefaction wave. The “Effective thickness” is defined as the critical plate thickness that ensures the rarefaction wave overtake the shock wave at the back of the sphere. The “Effective thickness” is directly related to the form of the debris cloud. The relation of the “Effective thickness” and the “Optimum thickness” is also discussed. The impacts of Al spheres onto Al plates are simulated within SPH to verify the propagation models and associated theories. The results show that the wave fronts predicted by the propagation models are closer to the simulation result at higher impact velocity. The curvatures of the wave fronts decrease with the increase of impact velocities. The predicted “Effective thickness” is consistent with the simulation results. The analysis about the shock wave propagation and unloading in this paper can provide a new sight and inspiration for the quantitative study of hypervelocity impact and space debris protection.     

A three‐stage procurement optimization problem under uncertainty

This article examines a problem faced by a firm procuring a material input or good from a set of suppliers. The cost to procure the material from any given supplier is concave in the amount ordered from the supplier, up to a supplier‐specific capacity limit. This NP‐hard problem is further complicated by the observation that capacities are often uncertain in practice, due for instance to production shortages at the suppliers, or competition from other firms. We accommodate this uncertainty in a worst‐case (robust) fashion by modeling an adversarial entity (which we call the “follower”) with a limited procurement budget. The follower reduces supplier capacity to maximize the minimum cost required for our firm to procure its required goods. To guard against uncertainty, the firm can “protect” any supplier at a cost (e.g., by signing a contract with the supplier that guarantees supply availability, or investing in machine upgrades that guarantee the supplier's ability to produce goods at a desired level), ensuring that the anticipated capacity of that supplier will indeed be available. The problem we consider is thus a three‐stage game in which the firm first chooses which suppliers' capacities to protect, the follower acts next to reduce capacity from unprotected suppliers, and the firm then satisfies its demand using the remaining capacity. We formulate a three‐stage mixed‐integer program that is well‐suited to decomposition techniques and develop an effective cutting‐plane algorithm for its solution. The corresponding algorithmic approach solves a sequence of scaled and relaxed problem instances, which enables solving problems having much larger data values when compared to standard techniques. © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013     

Nonrobustness of the normal approximation of lead‐time demand in a (Q,R) system

For computing an optimal (Q, R) or kindred inventory policy, the current literature provides mixed signals on whether or when it is safe to approximate a nonnormal lead‐time‐demand (“LTD”) distribution by a normal distribution. The first part of this paper examines this literature critically to justify why the issue warrants further investigations, while the second part presents reliable evidence showing that the system‐cost penalty for using the normal approximation can be quite serious even when the LTD‐distribution's coefficient of variation is quite low—contrary to the prevalent view of the literature. We also identify situations that will most likely lead to large system‐cost penalty. Our results indicate that, given today's technology, it is worthwhile to estimate an LTD‐distribution's shape more accurately and to compute optimal inventory policies using statistical distributions that more accurately reflect the LTD‐distributions' actual shapes. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

A branch‐and‐bound‐based solution approach for dynamic rerouting of airborne platforms

This article is a sequel to a recent article that appeared in this journal, “An extensible modeling framework for dynamic reassignment and rerouting in cooperative airborne operations” [ 17 ], in which an integer programming formulation to the problem of rescheduling in‐flight assets due to changes in battlespace conditions was presented. The purpose of this article is to present an improved branch‐and‐bound procedure to solve the dynamic resource management problem in a timely fashion, as in‐flight assets must be quickly re‐tasked to respond to the changing environment. To facilitate the rapid generation of attractive updated mission plans, this procedure uses a technique for reducing the solution space, supports branching on multiple decision variables simultaneously, incorporates additional valid cuts to strengthen the minimal network constraints of the original mathematical model, and includes improved objective function bounds. An extensive numerical analysis indicates that the proposed approach significantly outperforms traditional branch‐and‐bound methodologies and is capable of providing improved feasible solutions in a limited time. Although inspired by the dynamic resource management problem in particular, this approach promises to be an effective tool for solving other general types of vehicle routing problems. © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013     

基于模型诊断的集合逻辑运算法计算最小碰集

在基于模型的故障诊断仿真系统的诊断流程中,由最小冲突集计算最小碰集是整个流程中的关键步骤。针对现有计算最小碰集方法中存在的缺陷,提出了运用集合逻辑运算法计算最小碰集,将冲突集表示为集合的逻辑"与"、逻辑"或"运算,通过其运算法则进行运算简化,可得到全部的最小碰集。该方法具有简单有效、数据结构简单、计算简便快捷和易于程序实现等优点。最后通过实例计算,验证了该算法的正确性、简单性和高效性。     

A branch‐and‐price approach for the stochastic generalized assignment problem

In this article, we address a stochastic generalized assignment machine scheduling problem in which the processing times of jobs are assumed to be random variables. We develop a branch‐and‐price (B&P) approach for solving this problem wherein the pricing problem is separable with respect to each machine, and has the structure of a multidimensional knapsack problem. In addition, we explore two other extensions of this method—one that utilizes a dual‐stabilization technique and another that incorporates an advanced‐start procedure to obtain an initial feasible solution. We compare the performance of these methods with that of the branch‐and‐cut (B&C) method within CPLEX. Our results show that all B&P‐based approaches perform better than the B&C method, with the best performance obtained for the B&P procedure that includes both the extensions aforementioned. We also utilize a Monte Carlo method within the B&P scheme, which affords the use of a small subset of scenarios at a time to estimate the “true” optimal objective function value. Our experimental investigation reveals that this approach readily yields solutions lying within 5% of optimality, while providing more than a 10‐fold savings in CPU times in comparison with the best of the other proposed B&P procedures. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 131–143, 2014     

面向ACTD的主战坦克战法仿真方法及应用

主战坦克在论证研制阶段开展战场运用的战法研究,对于其定型和列装意义重大.提出一种基于CGF的战法仿真方法,并建立相应的战法仿真模型.最后,利用所研制的仿真系统,结合新型主战坦克的一种新战法进行了实例研究,并针对结果进行分析.该思路及仿真系统为新型主战坦克战法研究提供了简便高效的手段,可以满足面向先期概念演示验证中战法研究的需要.     

Appointment scheduling at a multidisciplinary outpatient clinic using stochastic programming

The purpose of this paper is to investigate the problem of constructing an appointment template for scheduling patients at a specific type of multidisciplinary outpatient clinic called an integrated practice unit (IPU). The focus is on developing and solving a stochastic optimization model for a back pain IPU in the face of random arrivals, an uncertain patient mix, and variable service times. The deterministic version of the problem is modeled as a mixed integer program with the objective of minimizing a weighted combination of clinic closing time (duration) and total patient waiting time (length of stay). A two‐stage stochastic program is then derived to account for the randomness and the sequential nature of the decisions. Although it was not possible to solve the two‐stage problem for even a limited number of scenarios, the wait‐and‐see (WS) problem was sufficiently tractable to provide a lower bound on the stochastic solution. The introduction of valid inequalities, limiting indices, and the use of special ordered sets helped to speed up the computations. A greedy heuristic was also developed to obtain solutions much more quickly. Out of practical considerations, it was necessary to develop appointment templates with time slots at fixed intervals, which are not available from the WS solution. The first to be derived was the expected value (EV) template that is used to find the expected value of the EV solution (EEV). This solution provides an upper bound on the objective function value of the two‐stage stochastic program. The average gap between the EEV and WS solutions was 18%. Results from extensive computational testing are presented for the EV template and for our adaptation of three other templates found in the literature. Depending on the relative importance of the two objective function metrics, the results demonstrate the trade‐off that exists between them. For the templates investigated, the “closing time” ranged from an average of 235 to 275 minutes for a 300‐minute session, while the corresponding “total patient time in clinic” ranged from 80 to 71 minutes.