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     

A stochastic assignment problem

There are n boxes with box i having a quota value Balls arrive sequentially, with each ball having a binary vector attached to it, with the interpretation being that if X_i = 1 then that ball is eligible to be put in box i. A ball's vector is revealed when it arrives and the ball can be put in any alive box for which it is eligible, where a box is said to be alive if it has not yet met its quota. Assuming that the components of a vector are independent, we are interested in the policy that minimizes, either stochastically or in expectation, the number of balls that need arrive until all boxes have met their quotas. © 2014 Wiley Periodicals, Inc. 62:23–31, 2015     

The United States and Humanitarian Assistance and Disaster Relief (HADR) in East Asia: Connecting Coercive and Non-Coercive Uses of Military Power

Abstract

Humanitarian Assistance and Disaster Relief (HADR) is increasingly important for East Asian militaries, but there is little scholarship on how HADR relates to broader national strategies. This article considers US involvement in HADR in East Asia in relation to changing conceptions of national power. HADR is frequently described as use of ‘hard’ military assets to further soft power goals. Looking at recent US experiences, this article shows that HADR also serves instrumental ends linked to traditional military objectives. Rather than considering power as ‘soft’ or ‘hard’, it argues that HADR illustrates connections between non-coercive and coercive uses of military power.     

Pakistan's Evolving Nuclear Weapon Posture

This essay provides an overview of the ongoing quantitative and qualitative changes in Pakistan's nuclear arsenal and their impact on deterrence stability vis-à-vis India. Prominent among these trends is a major expansion in fissile material production that enables the manufacture of lighter and more compact warheads optimized for battlefield missions; the development of cruise missiles and shorter-range ballistic missiles possessing dual-use capabilities; and a greater emphasis in doctrinal pronouncements on the need for strike options geared to all levels of conflict. Although these trends pose problematic ramifications for the risks of unauthorized and inadvertent escalation, deterrence stability in South Asia is not as precarious as many observers fear. The challenges of fashioning a robust nuclear peace between India and Pakistan cannot be lightly dismissed, however, and policy makers would do well to undertake some reinforcing measures.     

Critics gone wild: Counterinsurgency as the root of all evil

The Western interventions in Iraq and Afghanistan have produced a heated polemic concerning the merits and demerits of counterinsurgency – the operational approach underpinning both campaigns. The two books reviewed here provide a good summation of the arguments against counterinsurgency: it is not a strategy and will fail when mistaken as such; its theory does not make intervention and war significantly easier; and even the most successful counterinsurgency campaigns have been bloody, violent, and protracted. Yet as this review highlights, beyond these central points, criticism of counterinsurgency is too often off the mark in its approach and totalizing in its pretentions. There is much to criticize and an urgent need to learn from past campaigns, yet bold claims and broad generalizations can mislead rather than enlighten. The analysis is particularly unhelpful when the definition of the central issue at hand – counterinsurgency – is being unwittingly or deliberately distorted. In the end, these two books form a poor basis for the debate that must now take place, because they are too ideological in tone, too undisciplined in approach, and therefore too unqualified in what they finally say.     

Network routing for insurgency: An adversarial risk analysis framework

Problems in counterterrorism and corporate competition have prompted research that attempts to combine statistical risk analysis with game theory in ways that support practical decision making. This article applies these methods of adversarial risk analysis to the problem of selecting a route through a network in which an opponent chooses vertices for ambush. The motivating application is convoy routing across a road network when there may be improvised explosive devices and imperfect intelligence about their locations. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

Efficient sequential decision‐making algorithms for container inspection operations

Following work of Stroud and Saeger (Proceedings of ISI, Springer Verlag, New York, 2006) and Anand et al. (Proceedings of Computer, Communication and Control Technologies, 2003), we formulate a port of entry inspection sequencing task as a problem of finding an optimal binary decision tree for an appropriate Boolean decision function. We report on new algorithms for finding such optimal trees that are more efficient computationally than those presented by Stroud and Saeger and Anand et al. We achieve these efficiencies through a combination of specific numerical methods for finding optimal thresholds for sensor functions and two novel binary decision tree search algorithms that operate on a space of potentially acceptable binary decision trees. The improvements enable us to analyze substantially larger applications than was previously possible. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011