A best practice for assessment in counterinsurgency

In September 2011, the Commander of the International Security Assistance Force (ISAF) in Afghanistan directed the Afghan Assessment Group to redesign the way in which ISAF was assessing the status of the war, and to be ‘revolutionary’ in so doing. The resulting assessment paradigm was novel, non-doctrinal, and effectively addressed the unique complexities of the counterinsurgency in Afghanistan and the needs of the ISAF Commander. It had a two-tier structure consisting of both strategic and campaign assessments. The former focused on answering a set of strategic questions in narrative, analytic form to address the strategic environment, while the latter used a set of standards and accompanying narrative responses to gauge accomplishment of campaign tasks. Both tiers captured the current state of the war while maintaining an eye on future challenges and opportunities. The two assessments and their associated processes were designed to stimulate discussions leading directly to decisions by senior leaders on actions they could take, direct, or request. While any assessment paradigm will have advantages and disadvantages, an examination of the pros and cons of this assessment paradigm makes clear that it should be considered a ‘best practice’ in the field of counterinsurgency assessment.     

Optimality conditions for the bilevel programming problem

The bilevel programming problem (BLPP) is a sequence of two optimization problems where the constraint region of the first is determined implicitly by the solution to the second. In this article it is first shown that the linear BLPP is equivalent to maximizing a linear function over a feasible region comprised of connected faces and edges of the original polyhedral constraint set. The solution is shown to occur at a vertex of that set. Next, under assumptions of differentiability, first-order necessary optimality conditions are developed for the more general BLPP, and a potentially equivalent mathematical program is formulated. Finally, the relationship between the solution to this problem and Pareto optimality is discussed and a number of examples given.     

Challenges of measuring progress in Afghanistan using violence trends: the effects of aggregation,military operations,seasonality, weather,and other causal factors

Measuring nationwide progress of counterinsurgency operations in Afghanistan using violence trends is difficult due to several factors: aggregation of data to the national level may obfuscate disparate local trends; the observed seasonality in violence makes comparisons difficult and may obscure progress; and short-term spikes or troughs – attributable to weather, military operations and tempo, or holiday periods – heavily influence simple averaging schemes. Despite these challenges, proper understanding of violence statistics is critical to estimating the effectiveness of military forces added during a surge or redeployed as part of transition. This article explores methods for analyzing observed violence trends to identify causal factors, to provide a comparable baseline, and to inform assessments at appropriate levels of aggregation. One methodology for seasonal adjustment of violence data is discussed and shown to provide a logical baseline for examining trends. An ordinary least squares regression model is developed and implemented using time-series violence data.     

Computing equilibria via nonconvex programming

The problem of determining a vector that places a system in a state of equilibrium is studied with the aid of mathematical programming. The approach derives from the logical equivalence between the general equilibrium problem and the complementarity problem, the latter being explicitly concerned with finding a point in the set S = {x: < x, g(x)> = 0, g(x) ≦ 0, x ≧ 0}. An associated nonconvex program, min{? < x, g(x) > : g(x) ≦ 0, x ≧ 0}, is proposed whose solution set coincides with S. When the excess demand function g(x) meets certain separability conditions, equilibrium solutions are obtained by using an established branch and bound algorithm. Because the best upper bound is known at the outset, an independent check for convergence can be made at each iteration of the algorithm, thereby greatly increasing its efficiency. A number of examples drawn from economic and network theory are presented in order to demonstrate the computational aspects of the approach. The results appear promising for a wide range of problem sizes and types, with solutions occurring in a relatively small number of iterations.     

Appointment scheduling at a multidisciplinary outpatient clinic using stochastic programming

The purpose of this paper is to investigate the problem of constructing an appointment template for scheduling patients at a specific type of multidisciplinary outpatient clinic called an integrated practice unit (IPU). The focus is on developing and solving a stochastic optimization model for a back pain IPU in the face of random arrivals, an uncertain patient mix, and variable service times. The deterministic version of the problem is modeled as a mixed integer program with the objective of minimizing a weighted combination of clinic closing time (duration) and total patient waiting time (length of stay). A two‐stage stochastic program is then derived to account for the randomness and the sequential nature of the decisions. Although it was not possible to solve the two‐stage problem for even a limited number of scenarios, the wait‐and‐see (WS) problem was sufficiently tractable to provide a lower bound on the stochastic solution. The introduction of valid inequalities, limiting indices, and the use of special ordered sets helped to speed up the computations. A greedy heuristic was also developed to obtain solutions much more quickly. Out of practical considerations, it was necessary to develop appointment templates with time slots at fixed intervals, which are not available from the WS solution. The first to be derived was the expected value (EV) template that is used to find the expected value of the EV solution (EEV). This solution provides an upper bound on the objective function value of the two‐stage stochastic program. The average gap between the EEV and WS solutions was 18%. Results from extensive computational testing are presented for the EV template and for our adaptation of three other templates found in the literature. Depending on the relative importance of the two objective function metrics, the results demonstrate the trade‐off that exists between them. For the templates investigated, the “closing time” ranged from an average of 235 to 275 minutes for a 300‐minute session, while the corresponding “total patient time in clinic” ranged from 80 to 71 minutes.     

The Morale Maze: the German Army in Late 1918

The state of the German Army’s morale in 1918 is central to our understanding not only of the outcome of World War I, but also of the German Revolution and, indeed, through the pernicious ‘stab-in-the-back-myth’, on Weimar politics and the rise of the Nazis, too. This article presents new evidence from the German archives, blended with statistical analysis, to show that the morale of some units held up better than previously thought almost to the end, and thus to suggest three things. First, it proposes that some historians have placed too much reliance on English-language sources alone, such as British Army intelligence reports, which have various flaws as evidence. Second, it argues that, while historians have increasingly moved away from generalisations about German morale, this process has further to run. Third, it suggests that no single tipping point can be identified, and that morale alone does not provide a sufficient explanation for battlefield defeat. Indeed, much of the data can only be explained if the tactical realities of the war in late 1918 are clearly understood.     

In Search of the ‘X’ Factor: Morale and the Study of Strategy

A functional conceptualisation of morale is proposed, which focuses its meaning on motivation and the willingness to act rather than mood and group dynamics. Morale, it is argued, emerges from the subtle interrelationships of the many factors known to affect military means. It can be assessed both qualitatively and quantitatively, allowing the interaction between morale and policy to be explored in a manner that facilitates insight into the strategic process. A case study from the North African campaign of World War II is presented to explore in detail the relationship between morale and the art of war – strategy.