Service design at diagnostic service centers

We study a service design problem in diagnostic service centers, call centers that provide medical advice to patients over the phone about what the appropriate course of action is, based on the caller's symptoms. Due to the tension between increased diagnostic accuracy and the increase in waiting times more in‐depth service requires, managers face a difficult decision in determining the optimal service depth to guide the diagnostic process. The specific problem we consider models the situation when the capacity (staffing level) at the center is fixed, and when the callers have both congestion‐ and noncongestion‐related costs relating to their call. We develop a queueing model incorporating these features and find that the optimal service depth can take one of two different structures, depending on factors such as the nurses' skill level and the maximum potential demand. Sensitivity analyses of the two optimal structures show that they are quite different. In some situations, it may (or may not) be optimal for the manager to try to expand the demand at the center, and increasing skill level may (or may not) increase congestion. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

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     

Putin and Russia in retro and forward: the nuclear dimension

Deterioration in security relations as between NATO and Russia reached boiling point in the aftermath of Russia’s annexation of Crimea in 2014 and its subsequent destabilization of Eastern Ukraine. As a result, some voices in the West look forward to the departure of Vladimir Putin from power, and others to the possible disintegration of Russia as a unitary state. However, both the departure of Putin and the collapse of Russia have a nuclear dimension. Putin has issued pointed reminders of Russia’s status as a nuclear great power, and Russian military doctrine allows for nuclear first use in the event of a conventional war with extremely high stakes. Beyond Putin, a breakup of Russia would leave political chaos in Eastern Europe, Central Asia and elsewhere, inviting ambiguous command and control over formerly Russian nuclear forces.     

The equivalence of general set-covering and implicit integer programming formulations for shift scheduling

In a recent article we demonstrated that implicit optimal modeling for shift scheduling (P2) has inherent size and execution time advantages over the general set-covering formulation for shift scheduling (P1) [11, 13]. We postulated that the absence of extraordinary overlap (EO) was a requirement for the equivalence of P1 and P2. We have defined EO as the condition in which the earliest and latest starts for a break in one shift are earlier and later than the earliest and latest starts for a break in any other shift(s). In this article, we prove that our earlier postulate was accurate. Additionally, we discuss research extensions and note other scheduling problems for which implicit modeling may be appropriate. © 1996 John Wiley & Sons, Inc.     

How Is a Man to Decide? Unjust Combatants,Duress and McMahan’s Killing in War

Jeff McMahan’s much-discussed work Killing in War is an important part of the revisionist school of just war studies. This paper avoids discussion of McMahan’s use of human rights and examines the practical consequences of his argument about duress on soldiers to fight an unjust war. These arguments are found to be wanting and to be impractical ones that do not fit battlefield realities. The importance of the Law of Armed Conflict and the legal equality of combatants that is part of it is emphasised and accepted as the most practical way of regulating battlefield behaviour and saving lives. It is concluded that attempts to tell soldiers what to do when they may be fighting an unjust war add to their burdens and are misplaced.     

Beyond the Double Game: Lessons from Pakistan’s Approach to Islamist Militancy

States commonly take one of three approaches to militant groups on their soil: collaboration; benign neglect; or belligerence. All three approaches are present in Pakistan, where some groups also move back and forth among these categories. I employ the term “coopetition” to capture this fluidity. The dynamic nature of militancy in Pakistan makes the country an excellent laboratory for exploring a state’s assessment of the utility an Islamist militant group offers, and the threat it poses relative to other threats informs the state’s treatment of that group. In this article, I put forward a typology that situates Islamist militants in Pakistan in one of the above four categories. I also illustrate how a group’s identity, objectives, and alliances inform assessments of its utility and threat relative to other threats. In addition to enhancing our understanding of militant–state dynamics, this taxonomy builds on and helps to unify earlier typologies of Pakistani militancy.