Resilience in peacebuilding: Contesting uncertainty,ambiguity, and complexity

With the failure of liberal peace strategies in the Global South, resilience has recently become the risk management strategy par excellence in peacebuilding. Since it is not possible to predict when the next crisis will take place, peacebuilders must invest in bottom-up adaptive capacities to cope with external shocks. This article moves away from governmentality accounts of resilience which are overtly deterministic and depoliticizing. Instead, it posits that the uncertainty, ambiguity, and complexity associated with resilience mean that we should expect opportunities for contestation and institutional agency. This argument will be illustrated by drawing upon the European Union’s adoption of the resilience approach in its peacebuilding and security policies. The article argues that while uncertainty, ambiguity, and complexity constitute the ontological conditions that underpin the rise of resilience in peacebuilding, they are also likely to lead to its potential demise.     

Inference for the maximum cell probability under multinomial sampling

This article investigates inference for p_max, the largest cell probability in multinomial trials for the case of a small to moderate number of trials. Emphasis focuses on point and interval estimation. Both frequentist and Bayesian approaches are developed. The results of extensive simulation investigation are included as well as the analysis of a set of crime data for the city of New Orleans taken from the National Crime Survey.     

On the solution of a stochastic bottleneck assignment problem and its variations

In this article, we study the stochastic version of the so-called bottleneck assignment problem. Our primary objective is to maximize the probability that the bottleneck value satisfies a specified target. Under general stochastic assumptions, we show that the solution in this case is easily obtained by solving a linear assignment problem. We next examine the situation where the target is to be minimized, given that the probability of satisfying the target exceeds a specified threshold. Finally, we address extensions to the original problem where a second objective is also considered.     

Local search techniques for the generalized resource constrained project scheduling problem

In this article we address the problem of scheduling a single project network with both precedence and resource constraints through the use of a local search technique. We choose a solution definition which guarantees precedence feasibility, allowing the procedure to focus on overcoming resource infeasibility. We use the 110-problem data set of Patterson to test our procedure. Our results indicate a significant improvement over the best heuristic results reported to date for these problems (Bell and Han [1]). Two major advantages of the local search algorithm are its ability to handle arbitrary objective functions and constraints and its effectiveness over a wide range of problem sizes. We present a problem example with an objective function and resource constraints which include nonlinear and non-continuous components, which are easily considered by the procedure. The results of our algorithm are significantly better than random solutions to the problem. © 1993 John Wiley & Sons, Inc.     

The rise of targeted killing

Targeted killings have become a central tactic in the United States' campaigns against militant and terrorist groups in the Middle East, Asia, and Africa. Both ‘demand’ and ‘supply’ factors explain the rise of targeted killings. Demand for targeted killings increased as the United States faced new threats from militant groups that could not be effectively countered with conventional military force. Concerns about the political consequences of long-term military involvement overseas and American casualties led political leaders to supply more targeted killings. The conclusion discusses how this tactic may have unintended consequences as other states follow the United States use of targeted killings.