An informal framework to aid the analysis and design of military posture

The design of military posture is an exercise in confronting potential enemies’ capabilities within the context of geographic, technological, temporal, political and economic constraints. No formal model is capable of encapsulating the essentials of so complex an environment for closed or simulated analysis, but it is useful to have an informal framework within which to reason interactively within these dimensions.

This paper presents such a scaffolding, patterned on the notion of a military posture as the output of an economic process whose structure reflects important determinants of the characteristics and extents of weaponry and expenditures that are appropriate to the environment within the feasibility set determined by the constraints. The analysis remains at an abstract level, but it does highlight the important shifts toward preparation for littoral warfare, greater reliance on reserve rather than active forces, and necessary changes in missions among military departments.     

Machine maintenance with workload considerations

Machine maintenance is modeled in the setting of a single‐server queue. Machine deterioration corresponds to slower service rates and failure. This leads to higher congestion and an increase in customer holding costs. The decision‐maker decides when to perform maintenance, which may be done pre‐emptively; before catastrophic failures. Similar to classic maintenance control models, the information available to the decision‐maker includes the state of the server. Unlike classic models, the information also includes the number of customers in queue. Considered are both a repair model and a replacement model. In the repair model, with random replacement times, fixed costs are assumed to be constant in the server state. In the replacement model, both constant and variable fixed costs are considered. It is shown in general that the optimal maintenance policies have switching curve structure that is monotone in the server state. However, the switching curve policies for the repair model are not always monotone in the number of customers in the queue. Numerical examples and two heuristics are also presented. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

Colombian Military Thinking and the Fight against the FARC-EP Insurgency, 2002–2014

This article attempts to place in historical perspective the latest effort by Colombia’s military (Colmil) to defeat the now half century old insurgency of the Fuerzas Armadas Revolucionarias de Colombia – Ejército del Pueblo (FARC-EP). It argues that the ‘surge’ initiated under President Álvaro Uribe in 2002 with the assistance of the United States can only be fully analyzed in the context of the Colmil’s intellectual framework for counter-insurgency. Specifically, this article will explain how the protracted engagement with counter-insurgency has shaped the Colmil’s understanding of the nature of the conflict, as well as its attitudes towards its adversary, civil authority and the instrumentality of force. An understanding of the Colmil’s strategic tradition can also help to explain their apprehensions about the ongoing peace negotiations with the FARC-EP.     

When is model complexity too much? Illustrating the benefits of simple models with Hughes' salvo equations

The simulations that many defense analysts rely upon in their studies continue to grow in size and complexity. This paper contrasts the guidance that the authors have received—from some of the giants of military operations research—with the current practice. In particular, the analytic utility of Hughes' simple salvo equations is compared with that of the complex Joint Warfighting System (JWARS), with respect to JWARS' key performance parameters. The comparison suggests that a family of analytic tools supports the best analyses. It follows that smaller, more agile, and transparent models, such as Hughes' salvo equations, are underutilized in defense analyses. We believe that these models should receive more attention, use, and funding. To illustrate this point, this paper uses two very simple models (by modern standards) to rapidly generate insights on the value of information relative to force strength. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

Stochastic production capacity: A bane or a boon for quick response supply chains?

The quick response (QR) system that can cope with demand volatility by shortening lead time has been well studied in the literature. Much of the existing literature assumes implicitly or explicitly that the manufacturers under QR can always meet the demand because the production capacity is always sufficient. However, when the order comes with a short lead time under QR, availability of the manufacturer's production capacity is not guaranteed. This motivates us to explore QR in supply chains with stochastic production capacity. Specifically, we study QR in a two-echelon supply chain with Bayesian demand information updating. We consider the situation where the manufacturer's production capacity under QR is uncertain. We first explore how stochastic production capacity affects supply chain decisions and QR implementation. We then incorporate the manufacturer's ability to expand capacity into the model. We explore how the manufacturer determines the optimal capacity expansion decision, and the value of such an ability to the supply chain and its agents. Finally, we extend the model to the two-stage two-ordering case and derive the optimal ordering policy by dynamic programming. We compare the single-ordering and two-ordering cases to generate additional managerial insights about how ordering flexibility affects QR when production capacity is stochastic. We also explore the transparent supply chain and find that our main results still hold.     

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     

境外行政主体制度研究

行政主体理论自行政法成为公法重要组成部分时便成为行政法几个核心理论之一。自《中华人民共和国行政诉讼法》实施以来,行政主体理论研究成为我国行政法理论研究的重点之一。我国关于行政主体的内涵及外延,学术界各抒己见,至今缺乏统一的论断。境外一些行政法理论发达国家和地区的行政主体制度对于我们具有借鉴意义。