NUCLEAR ATTRIBUTION AS DETERRENCE

Recently, post-explosion nuclear forensics, or nuclear attribution, has gained a new spotlight within the nuclear weapons scientific and policymaking community. Academics are beginning to ask whether post-explosion forensics might create a replacement for an international nonproliferation regime, or at least offer a fallback option to deter states and individuals from selling nuclear materials. This paper examines current attribution technology from unclassified literature and finds the technology to be well developed but not foolproof, such that nuclear attribution currently provides little deterrent value. If current capabilities were publicized more thoroughly and if the post-explosion process of assessing the evidence were internationalized, states and intermediate actors might be deterred more effectively. Developing a nuclear fingerprint database is also discussed. While useful, its impact on deterrence would be minimal.     

IF YOU WANT IT DONE RIGHT,DO IT YOURSELF

Some have argued that the transatlantic rancor over the Iraq war made cooperation, especially on nonproliferation, unlikely. In contrast, this article, documents post-invasion instances of nonproliferation cooperation, with particular emphasis on the Proliferation Security Initiative and the EU-3 Initiative—the British, French, and German negotiations with Iran over its suspected nuclear activities. In addition to documenting French and British participation in these initiatives, the article analyzes why they have chosen to participate and argues that France and Britain have participated in both efforts because they are committed to avoiding future Iraq-like preventive wars.     

Optimization of steerable sensor network for threat detection

A Markov chain approach to detecting a threat in a given surveillance zone by a network of steerable sensors is presented. The network has a finite number of predetermined states, and transition from one state to another follows a Markov chain. Under the assumption that the threat avoids detection, two game theoretic problems for finding an optimal Markov chain (two surveillance strategies) are formulated: the first maximizes the probability of threat detection for two consecutive detection periods, whereas the second minimizes the average time of detection for the worst‐case threat's trajectory. Both problems are reduced to linear programming, and special techniques are suggested to solve them. For a dynamic environment with moving noise sources, the optimal Markov chain changes at each detection period, and the rate of convergence of the Markov chain to its stationary distribution is analyzed. Both surveillance strategies are tested in numerical experiments and compared one with another. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

On optimal system designs in reliability‐economics frameworks

Reliability Economics is a field that can be defined as the collection of all problems in which there is tension between the performance of systems of interest and their cost. Given such a problem, the aim is to resolve the tension through an optimization process that identifies the system which maximizes some appropriate criterion function (e.g. expected lifetime per unit cost). In this paper, we focus on coherent systems of n independent and identically distributed (iid) components and mixtures thereof, and characterize both a system's performance and cost as functions of the system's signature vector (Samaniego, IEEE Trans Reliabil (1985) 69–72). For a given family of criterion functions, a variety of optimality results are obtained for systems of arbitrary order n. Approximations are developed and justified when the underlying component distribution is unknown. Assuming the availability of an auxiliary sample of N component failure times, the asymptotic theory of L‐estimators is adapted for the purpose of establishing the consistency and asymptotic normality of the proposed estimators of the expected ordered failure times of the n components of the systems under study. These results lead to the identification of ε‐optimal systems relative to the chosen criterion function. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

Optimal shift scheduling: A branch‐and‐price approach

We present a branch‐and‐price technique for optimal staff scheduling with multiple rest breaks, meal break, and break windows. We devise and implement specialized branching rules suitable for solving the set covering type formulation implicitly, using column generation. Our methodology is more widely applicable and computationally superior to the alternative methods in the literature. We tested our methodology on 365 test problems involving between 1728 and 86400 shift variations, and 20 demand patterns. In a direct comparison with an alternative method, our approach yields significant improvements both in cpu time and in the number of problem instances solved to optimality. The improvements were particularly marked for problems involving larger numbers of feasible shifts. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 185–200, 2000     

Note: A local-search heuristic for large set-covering problems

In this note we describe a local-search heuristic (LSH) for large non-unicost set-covering problems (SCPs). The new heuristic is based on the simulated annealing algorithm and uses an improvement routine designed to provide low-cost solutions within a reasonable amount of CPU time. The solution costs associated with the LSH compared very favorably to the best previously published solution costs for 20 large SCPs taken from the literature. In particular, the LSH yielded new benchmark solutions for 17 of the 20 test problems. We also report that, for SCPs where column cost is correlated with column coverage, the new heuristic provides solution costs competitive with previously published results for comparable problems. © 1995 John Wiley & Sons, Inc.