Drone Strikes and Grand Strategy: Toward a Political Understanding of the Uses of Unmanned Aerial Vehicle Attacks in US Security Policy

This article analyzes the political utility of US drone strikes theoretically and deductively. Placing strikes within the context of the theorized political functions of force and considering how they fit into two grand strategies, restraint and selective engagement, I argue that these strikes buy the United States relatively little in the way of political effects assuring its own security because the terrorism threat they are intended to combat is a limited one within the skein of US global interests. Furthermore, their contribution to counter-terrorism efforts is likely to diminish with the adoption of armed drones by non-state actors. Drone strikes can, however, provide leverage over recalcitrant US client states while reassuring liberal partners and giving them some leverage over US choices. In addition, within the counter-terrorism sphere, drone strikes are less likely to inflame popular opinion than are alternative uses of force. This analysis contributes to an increasingly rigorous examination of the strikes’ role in US foreign and security policy.     

To catch an intruder: Part A—uncluttered scenario

We analyze an interdiction scenario where an interceptor attempts to catch an intruder as the intruder moves through the area of interest. A motivating example is the detection and interdiction of drug smuggling vessels in the Eastern Pacific and Caribbean. We study two models in this article. The first considers a nonstrategic target that moves through the area without taking evasive action to avoid the interdictor. We determine the optimal location the interceptor should position itself to best respond when a target arrives. The second model analyzes the strategic interaction between the interceptor and intruder using a Blotto approach. The intruder chooses a route to travel on and the interceptor chooses a route to patrol. We model the interaction as a two‐player game with a bilinear payoff function. We compute the optimal strategy for both players and examine several extensions. © 2017 Wiley Periodicals, Inc. Naval Research Logistics, 64: 29–40, 2017     

India nuclear weapons: No first use or no full disclosure?

This article argues India is laying the foundation to move away from “no-first-use” (NFU) as its nuclear weapons employment policy. Since the inception of its nuclear weapons program, India has claimed NFU as the centerpiece of its nuclear strategy. But India has a history of developing foundational changes to its nuclear weapons program before such changes actually occur. For example, the infrastructure of India’s nuclear weapons program was already being created in the 1950s under the guise of civilian nuclear power. Similarly, the weaponization of India’s program, which did not officially occur until after the 1998 tests, had its genesis in far earlier decisions. A close examination of trends in India’s nuclear weapons production complex, its delivery systems, and its command and control complex all lead to the conclusion that India is laying the groundwork for more flexible employment options, up to and including first use. This article does not argue such a decision has been taken. Rather, it argues the underpinning is in place to allow for a move to more flexible options, perhaps very quickly, at some point in the future. This could occur during crisis or it could occur incrementally over time.     

Note: “Simultaneous optimization of efficiency and performance balance measures in single-machine scheduling problems”

n independent jobs are to be scheduled nonpreemptively on a single machine so as to minimize some performance measure. Federgruen and Mosheiov [2] show that a large class of such scheduling problems can be optimized by solving either a single instance or a finite sequence of instances of the so-called SQC problem, in which all the jobs have a fixed or controllable common due date and the sum of general quasiconvex functions of the job completion times is to be minimized. In this note we point out that this is not always true. In particular, we show that the algorithm proposed in [2] does not always find a global optimal schedule to the problem of minimizing the weighted sum of the mean and variance of job completion times. © 1996 John Wiley & Sons, Inc.