From the ESS to the EU Global Strategy: external policy,internal purpose

Security strategies are important sites for narrating the EU into existence as a security actor. The unveiling of a new global strategy on foreign and security policy for the EU immediately post-Brexit could be conceived as a pledge to remain together as a Union for the purposes of contributing to global security in a particular way. This paper offers a brief stock-taking of the EU’s way of writing security from the European Security Strategy (2003) to the EU Global Strategy (2016). A concise exegesis of these documents exposes an interesting dynamic: as exercises in ordering the world, both strategic guidelines have turned out to be major exercises in ordering the self. The comparative snapshot shows the EU as increasingly anxious to prove its relevance for its own citizens, yet notably less confident about its actual convincingness as an ontological security framework for the EU’s constituent members over time.     

Learning to Fight and Fighting to Learn: Practitioners and the Role of Unit Publications in VIII Fighter Command 1943–1944

A military cannot hope to improve in wartime if it cannot learn. Ideally, in wartime, formal learning ceases and the application of knowledge begins. But this is optimistic. In 1942, USAAF Eighth Air Force assumed it had the means necessary for victory. In reality, its technique and technology were only potentially – rather than actually – effective. What remained was to create the practice of daylight bombing – to learn. This article (1) recovers a wartime learning process that created new knowledge, (2) tests existing tacit hypotheses in military adaptation research, and (3) offers additional theoretical foundation to explain how knowledge is created in wartime     

An optimal critical level policy for inventory systems with two demand classes

Traditional inventory systems treat all demands of a given item equally. This approach is optimal if the penalty costs of all customers are the same, but it is not optimal if the penalty costs are different for different customer classes. Then, demands of customers with high penalty costs must be filled before demands of customers with low penalty costs. A commonly used inventory policy for dealing with demands with different penalty costs is the critical level inventory policy. Under this policy demands with low penalty costs are filled as long as inventory is above a certain critical level. If the inventory reaches the critical level, only demands with high penalty costs are filled and demands with low penalty costs are backordered. In this article, we consider a critical level policy for a periodic review inventory system with two demand classes. Because traditional approaches cannot be used to find the optimal parameters of the policy, we use a multidimensional Markov chain to model the inventory system. We use a sample path approach to prove several properties of this inventory system. Although the cost function is not convex, we can build on these properties to develop an optimization approach that finds the optimal solution. We also present some numerical results. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

Algorithm to solve a chance‐constrained network capacity design problem with stochastic demands and finite support

We consider the problem of determining the capacity to assign to each arc in a given network, subject to uncertainty in the supply and/or demand of each node. This design problem underlies many real‐world applications, such as the design of power transmission and telecommunications networks. We first consider the case where a set of supply/demand scenarios are provided, and we must determine the minimum‐cost set of arc capacities such that a feasible flow exists for each scenario. We briefly review existing theoretical approaches to solving this problem and explore implementation strategies to reduce run times. With this as a foundation, our primary focus is on a chance‐constrained version of the problem in which α% of the scenarios must be feasible under the chosen capacity, where α is a user‐defined parameter and the specific scenarios to be satisfied are not predetermined. We describe an algorithm which utilizes a separation routine for identifying violated cut‐sets which can solve the problem to optimality, and we present computational results. We also present a novel greedy algorithm, our primary contribution, which can be used to solve for a high quality heuristic solution. We present computational analysis to evaluate the performance of our proposed approaches. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 236–246, 2016     

Northern Ireland and minimum force: the refutation of a concept?

The debate over whether there exists a British counter-insurgency tradition of minimum force is one that has been thoroughly discussed. Is there anything left to say? This study suggests there is further insight to be attained if one explicitly evaluates the concept of minimum force in relation to the conduct of the security forces in the years of the Northern Ireland conflict. Through an examination of three key periods in the conflict, it will be shown that while there was invariably an awareness of the need to act with restraint among senior officers at the strategic level, this was often difficult to apply at the tactical level in the heat of confrontation. The argument demonstrates that the British Army, and other instruments of the state, rarely acted in a manner that could be described as ‘minimal’. Instead, it was the broader liberal values of the British state that explains largely the degrees of restraint exhibited by the government and security forces.     

Scheduling customer arrivals to a stochastic service system

An efficient algorithm for determining the optimal arrival schedule for customers in a stochastic service system is developed. All customers arrive exactly when scheduled, and service times are modeled as iid Erlang random variables. Costs are incurred at a fixed rate per unit of time each customer waits for service, and an additional cost is incurred for every unit of time the server operates beyond a scheduled closing time. The objective is to minimize total operating cost. This type of problem arises in many operational contexts including transportation, manufacturing, and appointment‐based services. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 549–559, 1999