Determining crane areas for balancing workload among interfering and noninterfering cranes

This article treats the problem of subdividing an area for storing containers such that the workload is evenly shared among the cranes operating the resulting subareas. We consider two crane sets: while noncrossing constraints between cranes of the same set need to be observed, cranes of different sets do not interfere. Such a problem setting is, for instance, relevant for scheduling the (un‐)loading of vessels by parallel quay cranes operating on opposing berths or in container yards with cross‐over cranes. We formalize the resulting optimization problem, prove computational complexity, and present exact and heuristic solution procedures. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

Lagrangian solution of maximum dispersion problems

We address the so‐called maximum dispersion problems where the objective is to maximize the sum or the minimum of interelement distances amongst a subset chosen from a given set. The problems arise in a variety of contexts including the location of obnoxious facilities, the selection of diverse groups, and the identification of dense subgraphs. They are known to be computationally difficult. In this paper, we propose a Lagrangian approach toward their solution and report the results of an extensive computational experimentation. Our results show that our Lagrangian approach is reasonably fast, that it yields heuristic solutions which provide good lower bounds on the optimum solution values for both the sum and the minimum problems, and further that it produces decent upper bounds in the case of the sum problem. For the sum problem, the results also show that the Lagrangian heuristic compares favorably against several existing heuristics. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 97–114, 2000     

Enhancing Political Cohesion in NATO during the 1950s or: How it Learned to Stop Worrying and Love the (Tactical) Bomb

This article argues that the perceived need by NATO to nurture political cohesion within the Alliance during the 1950s resulted in the adoption of strategic concepts that were out-of-step with the military environment in which it was operating. It maintains that the Alliance acquiesced to American leadership on nuclear issues which led to the development of tactical nuclear capabilities at the expense of conventional war-fighting capabilities for the defence of the European Central Front. This resulted in a strategic concept that enhanced political cohesion but was militarily unviable.     

A forward network simplex algorithm for solving multiperiod network flow problems

An optimization model which is frequently used to assist decision makers in the areas of resource scheduling, planning, and distribution is the minimum cost multiperiod network flow problem. This model describes network structure decision-making problems over time. Such problems arise in the areas of production/distribution systems, economic planning, communication systems, material handling systems, traffic systems, railway systems, building evacuation systems, energy systems, as well as in many others. Although existing network solution techniques are efficient, there are still limitations to the size of problems that can be solved. To date, only a few researchers have taken the multiperiod structure into consideration in devising efficient solution methods. Standard network codes are usually used because of their availability and perceived efficiency. In this paper we discuss the development, implementation, and computational testing of a new technique, the forward network simplex method, for solving linear, minimum cost, multiperiod network flow problems. The forward network simplex method is a forward algorithm which exploits the natural decomposition of multiperiod network problems by limiting its pivoting activity. A forward algorithm is an approach to solving dynamic problems by solving successively longer finite subproblems, terminating when a stopping rule can be invoked or a decision horizon found. Such procedures are available for a large number of special structure models. Here we describe the specialization of the forward simplex method of Aronson, Morton, and Thompson to solving multiperiod network network flow problems. Computational results indicate that both the solution time and pivot count are linear in the number of periods. For standard network optimization codes, which do not exploit the multiperiod structure, the pivot count is linear in the number of periods; however, the solution time is quadratic.     

Callwell versus Graziani: how the British Army applied ‘small wars’ techniques in major operations in Africa and the Middle East, 1940–41

The period from December 1940 through to the spring of 1941 saw the British Army win a series of rapid and decisive victories over Italian and Vichy French forces in North and East Africa and the Middle East. A key feature of these operations was the extensive British use of fast-moving all-arms mobile formations utilising superior speed and mobility to out-manoeuvre considerably larger Italian formations. A number of reasons have been given for the British Army adopting this mode of warfare, but the paper contends that the best explanation is that they were an organic evolution from methods used by the British Army in ‘small wars’ throughout the early twentieth century, use of mobile ‘frontier columns’ at the operational and tactical level of war being described and recommended by Callwell himself and visible with the Army in practice in operations in India and the Middle East in particular. The inter-war period saw the combination of this model of warfare with post-First World War military technology, notably tanks, close air support and coordination by wireless. Colonial operations in this period also saw some utilisation of what would later be identified as ‘Special Forces’ – also used extensively in the Desert War – the most obvious example being Captain Orde Wingate's Special Night Squads in Palestine in 1938.     

Cognitivism,prospect theory,and foreign policy change: a comparative analysis of the politics of counterinsurgency in Malaya and Afghanistan

This article investigates the cognitive limitations on policy change in counterinsurgency (COIN) efforts by examining why American decision-makers failed to revise their government strategy substantially while fighting the insurgency in Afghanistan in 2003–2014 and why their British counterparts were more successful in adjusting their policies in the Malayan insurgency in 1948–1954. Unlike most of the COIN literature that concentrates on military strategy and tactics, the analysis of government policy-making in Malaya holds some important political lessons for American leaders today despite differences between the insurgencies in Afghanistan and British Malaya. As a response to the criticism of COIN studies in general that they lack theoretical guidance, this article utilizes an integrated cognitivist-prospect theory framework. It is argued that some of the COIN literature mistakenly suggests that a more difficult strategic situation was primarily responsible for American failure in Afghanistan. Instead, American decision-makers faced a more difficult task cognitively than their British counterparts, as policy change in Afghanistan would have required greater ideational change. American principals were much more attached to their beliefs emotionally, had no alternative problem representation, and had to shift between frames in order to engineer a response that was more in line with events on the ground in Afghanistan. Regarding prospect theory, findings indicate that gains frames appear to be unhelpful in monitoring progress until catastrophic failure endangers the reference point, and that decision-makers often have more than one reference point to attune their policies to, which often results in suboptimal choices with regard to at least one reference point.     

Robust tower location for code division multiple access networks

Designing Code Division Multiple Access networks includes determining optimal locations of radio towers and assigning customer markets to the towers. In this paper, we describe a deterministic model for tower location and a stochastic model to optimize revenue given a set of constructed towers. We integrate these models in a stochastic integer programming problem with simple recourse that optimizes the location of towers under demand uncertainty. We develop algorithms using Benders' reformulation, and we provide computational results. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007