Between a rock and a hard place: Europe in a post-INF world

The end of the 1987 Intermediate-range Nuclear Forces (INF) Treaty has the potential to plunge Europe and NATO into deep crisis. Russia’s continued violation coupled with the Donald J. Trump administration’s desire to balance against Moscow and Beijing could force a new missile debate on Europeans. Even though Washington is trying to assuage its allies, the specter of another round of INF missile deployments to Europe is not unrealistic. Meanwhile, NATO’s European members face a dilemma. Some want NATO to resolutely push back against Russia. Others want to avoid a new deployment debate, at almost all costs. The Kremlin will use these cleavages to weaken NATO. If not carefully handled, NATO’s response to the Russian missile buildup could lead to domestic turmoil in a number of European states and render the alliance ineffective for a prolonged period. Europeans need to act now and voice their preferences in the military and diplomatic domains. A number of different military options are available, below the level of deploying new INF missiles in Europe. However, Europeans need to consider trade-offs regarding crisis and arms-race stability. At the same time, it will be up to European capitals to conceptualize a new arms-control framework for the post-INF world, one that takes into account today’s geopolitical realities and the entanglement of modern conventional and nuclear forces. Given the Trump administration’s loathing of arms control, concepts of mutual restraint may well have to wait for the next US administration. In any case, that should not stop Europeans from taking on more responsibility for their own security.     

Can Limited Intervention Work? Lessons from Britain’s Success Story in Sierra Leone

ABSTRACT

Following frustrating campaigns in Iraq and Afghanistan, Western interventions are becoming more limited, with troops being deployed for short bursts and residual peace-building tasks being left to others. Although this approach limits exposure for the intervening government, it struggles to achieve meaningful political change. Examining the comparatively successful British intervention in Sierra Leone (2000–02), this article identifies the conditions for effectiveness in these campaigns. It challenges the historiography of the case by framing armed confrontations and raids as enablers of politics rather than ends in themselves; indeed, in both the conduct and study of intervention, politics must reign supreme.     

Interactive multicriteria linear programming: An extension of the method of Zionts and Wallenius

This article presents an extension of the interactive multicriteria linear-programming method of Zionts and Wallenius [see Management Science, 29 (5) (1983)]. The decision maker's underlying utility function is assumed to be pseudoconcave, and his preference structure is assessed through pairwise comparison questions. In the method of Zionts and Wallenius, the decision maker's preference structure is represented as constraints on the weights on the objectives derived from his responses. This representation is only a linear approximation to the underlying nonlinear utility function. Accordingly, inconsistency among the constraints on the weights arises while solving the problem. Therefore, some of the constraints have to be dropped, resulting in a loss of information on the preference structure, and hence an increase in the total number of questions. In this article we develop a hybrid representation scheme to avoid this problem. The proposed scheme is implemented within the algorithmic framework of the method of Zionts and Wallenius, and its underlying theory is developed. Computational results show that the number of questions required by the Zionts and Wallenius method can be sinificantly reduced using the proposed scheme.     

Preventing conflict upstream: impunity and illicit governance across Colombia’s borders

This article explores how transnational borderlands matter for conflict prevention and, in particular, so-called upstream engagement, which aims to reduce threats to global stability and security that arise from the world’s increasing interconnectedness. Accounting for transnational borderlands in vulnerable regions is crucial for conflict prevention as pursued by the defence and security sector because borderlands are catalysts of the negative side of global interconnectedness: they are business hubs for transnational organised crime, sites of retreat for conflict actors, and safe havens for terrorists. The border areas’ proneness to impunity and the ability of violent non-state actors to govern these spaces illicitly contribute to the emergence of these characteristics. I therefore argue that upstream conflict prevention needs to do two things to address these risks: first, to overcome a national security approach centred on the borderline and instead acknowledge transnational security dynamics in borderlands on both sides of the border; second, to overcome the state-centred governance lens to also consider governance exerted by non-state actors. The article draws on empirical data from a six-year study including over a year of fieldwork in and on Colombia’s borderlands.     

Is human trafficking the dark side of economic freedom?

Economic freedom has increased living standards worldwide. Concurrent with such gains are rising concerns about potential human costs associated with free markets. This paper uses data on human trafficking and anti-trafficking policies, in conjunction with a measure of economic freedom, to examine whether free markets exacerbate or attenuate the incidence of human trafficking and policies designed to combat it. We do not find evidence suggesting that economic freedom is associated with human trafficking. In addition, our results suggest that economically free countries are more likely to enact and enforce policies to fight human trafficking.     

A heuristic method for facility planning in telecommunications networks with multiple alternate routes

Given point-to-point demand forecasts of transmission facilities for services such as voice or data transmission in each period of a finite planning horizon, a decision has to be made as to which types of transmission facilities—together with the amounts of transmission circuits—are to be installed, if any, on each link of the telecommunications network, in each period of the planning horizon. The availability of alternative transmission systems with significantly different costs and circuit capacities necessitates the determination of a minimum (discounted) cost facility installation scheme. This combinatoric choice problem is complicated by the availability of switching equipments enabling the transmission of some of the traffic through intermediary points. This possibility of alternately routing the traffic or the facility requirements of certain point pairs further complicates the problem while creating the opportunity to benefit from economies of scale. We present here a heuristic method for finding a good solution for the general problem; namely, we consider multiple transmission systems and multiple alternate routes. Numerical examples are given and computational experience is reported.     

Probability inequalities via negative dependence for random variables conditioned on order statistics

Distributions are studied which arise by considering independent and identically distributed random variables conditioned on events involving order statistics. It is shown that these distributions are negatively dependent in a very strong sense. Furthermore, bounds are found on the distribution functions. The conditioning events considered occur naturally in reliability theory as the time to system failure for k-out-of-n systems. An application to systems formed with “second-hand” components is given.     

An extensible modeling framework for dynamic reassignment and rerouting in cooperative airborne operations

Unmanned aerial vehicles (UAVs), increasingly vital to the success of military operations, operate in a complex and dynamic environment, sometimes in concert with manned aircraft. We present an extensible modeling framework for the solution to the dynamic resource management (DRM) problem, where airborne resources must be reassigned to time‐sensitive tasks in response to changes in battlespace conditions. The DRM problem is characterized by diverse tasks with time windows, heterogeneous resources with fuel‐ and payload‐capacity limitations, and multiple competing objectives. We propose an integer linear programing formulation for this problem, where mathematical feasibility is guaranteed. Although motivated by airborne military operations, the proposed general modeling framework is applicable to a wide array of settings, such as disaster relief operations. Additionally, land‐ or water‐based operations may be modeled within this framework, as well as any combination of manned and unmanned vehicles. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

Doubly Stochastic Sequential Assignment Problem

This article introduces the Doubly Stochastic Sequential Assignment Problem (DSSAP), an extension of the Sequential Stochastic Assignment Problem (SSAP), where sequentially arriving tasks are assigned to workers with random success rates. A given number of tasks arrive sequentially, each with a random value coming from a known distribution. On a task arrival, it must be assigned to one of the available workers, each with a random success rate coming from a known distribution. Optimal assignment policies are proposed for DSSAP under various assumptions on the random success rates. The optimal assignment algorithm for the general case of DSSAP, where workers have distinct success rate distribution, has an exponential running time. An approximation algorithm that achieves a fraction of the maximum total expected reward in a polynomial time is proposed. The results are illustrated by several numerical experiments. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 124–137, 2016     

Approximation algorithms for sequential batch‐testing of series systems

We introduce and study a generalization of the classic sequential testing problem, asking to identify the correct state of a given series system that consists of independent stochastic components. In this setting, costly tests are required to examine the state of individual components, which are sequentially tested until the correct system state can be uniquely identified. The goal is to propose a policy that minimizes the expected testing cost, given a‐priori probabilistic information on the stochastic nature of each individual component. Unlike the classic setting, where variables are tested one after the other, we allow multiple tests to be conducted simultaneously, at the expense of incurring an additional set‐up cost. The main contribution of this article consists in showing that the batch testing problem can be approximated in polynomial time within factor , for any fixed . In addition, we explain how, in spite of its highly nonlinear objective function, the batch testing problem can be formulated as an approximate integer program of polynomial size, while blowing up its expected cost by a factor of at most . Finally, we conduct extensive computational experiments, to demonstrate the practical effectiveness of these algorithms as well as to evaluate their limitations. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 275–286, 2016