To Protect and Serve: Civilian Policing and the United Nations Mission in Kosovo

Since the end of the Cold War the process of nation building has become a priority in the attempt to maintain world order and security in the wake of the instability and devastation wrought by failed and war-torn states. The proliferation of nation-building missions has led to their diversification and the need to marshal a vast array of resources in order to attain substantial levels of success. This article deals with a new and important component of peacekeeping and nation-building missions, that of civilian policing. The article outlines the goals of using civilian police officers in nation-building missions and discusses a variety of problems (pragmatic, legal, and cultural) that policing may introduce to such missions. This discussion is focused around the civilian policing component of the United Nations Mission in Kosovo. It delineates the successes and hardships so far experienced during the mission in Kosovo and explores the insights that the mission may provide for similar projects in the future.     

Applying Order-of-Battle to Al Qaeda Operations

Since the global war on terror began, the pursuit of Al Qaeda is widely considered as warfare and not the pursuit of criminals. In light of counter-terrorism being redefined as war, the criteria applied for tracking militaries of conventional enemies may also be applicable to Al Qaeda. Intelligence analysts have long used the nine order-of-battle (OB) criteria as part of the estimative process for conventional, or nation-state, enemies. Applying OB criteria to Al Qaeda may assist intelligence analysts in knowing the enemy and identifying changes that will allow for predictive analysis. Many elements of Al Qaeda's OB prior to the events of 11 September were viewed as clutter and not significant changes that might have otherwise alerted intelligence analysts to the impending attack. This essay suggests how one might go about applying the nine OB criteria to analysis of Al Qaeda. Although more difficult and requiring modification, using an analytical procedure that has been tested successfully over many years is a logical step in the war on Al Qaeda. If all OB changes are tracked and analyzed using a systematic approach as outlined in this essay, Al Qaeda attacks may be predicted and/or curtailed in the future.     

The capital supply curve in capacity expansion models: Some economic and algorithmic aspects

Capacity expansion models typically minimize the discounted cost of acquisition and operation over a given planning horizon. In this article we generalize this idea to one in which a capital supply curve replaces the usual discount rate. A capital supply curve is a means to model financial outlook, investment limits, and risk. We show that when such a curve is included in a capacity expansion model, it will, under certain conditions, provide a less capital intensive solution than one which incorporates a discount rate. In this article, we also provide an algorithm that solves capacity expansion models that incorporate a capital supply curve. The attractive feature of this algorithm is that it provides a means to utilize the “discount rate” models efficiently. Throughout, we give applications in power generation planning and computational experience for this application is also presented.     

Continuous-time markov decision processes with nonzero terminal reward

In this article we consider a continuous-time Markov decision process with a denumerable state space and nonzero terminal rewards. We first establish the necessary and sufficient optimality condition without any restriction on the cost functions. The necessary condition is derived through the Pontryagin maximum principle and the sufficient condition, by the inherent structure of the problem. We introduce a dynamic programming approximation algorithm for the finite-horizon problem. As the time between discrete points decreases, the optimal policy of the discretized problem converges to that of the continuous-time problem in the sense of weak convergence. For the infinite-horizon problem, a successive approximation method is introduced as an alternative to a policy iteration method.     

An analysis of constrained robust regression estimators

Multicollinearity and nonnormal errors are problems often encountered in the application of linear regression. Estimators are proposed for dealing with the simultaneous occurrence of both multicollinearity and nonnormality. These estimators are developed by combining biased estimation techniques with certain robust criteria. An iteratively reweighted least-squares procedure is used to compute the estimates. The performance of the combined estimators is studied empirically through Monte Carlo experiments structured according to factorial designs. With respect to a mean-squared-error criterion, the combined estimators are superior to ordinary least-squares, pure biased estimators, and pure robust estimators when multicollinearity and nonnormality are present. The loss in efficiency for the combined estimators relative to least squares is small when these problems do not occur. Some guidelines for the use of these combined estimators are given.     

Multiechelon repairable-item provisioning in a time-varying environment using the randomization technique

Multiechelon repairable-item provisioning systems are considered under a time-varying environment. Such conditions could arise, for example, in a military context where a shift from peacetime operation to wartime operation takes place; or, in a civilian setting where a public transit system decides to increase its hours of operation or frequency of service. Exact Markovian models, incorporating a finite population of repairable components and limited repair capacity (nonample service), are treated, with transient solutions obtained using the randomization technique. The exact models are compared with the approximate Dyna-METRIC model which assumes an infinite population of components and ample repair capacity.