Nuclear opportunism: A theory of how states use nuclear weapons in international politics

How do states use nuclear weapons to achieve their goals in international politics? Nuclear weapons can influence state decisions about a range of strategic choices relating to military aggression, the scope of foreign policy objectives, and relations with allies. The article offers a theory to explain why emerging nuclear powers use nuclear weapons to facilitate different foreign policies: becoming more or less aggressive; providing additional support to allies or proxies, seeking independence from allies; or expanding the state’s goals in international politics. I argue that a state’s choices depend on the presence of severe territorial threats or an ongoing war, the presence of allies that provide for the state’s security, and whether the state is increasing in relative power. The conclusion discusses implications of the argument for our understanding of nuclear weapons and the history of proliferation, and nonproliferation policy today.     

More military base closure? Considering the alternatives*

Despite multiple base closing rounds, the United States Department of Defense still has excess base capacity, and thus President Trump and high-level Defense Department officials are calling for more base closure through the Base Realignment and Closure (BRAC) process. However, another BRAC may not be the optimal solution, because simple base closure is not an efficient way to reduce surplus base capacity. Thus, Defense Department officials should consider other methods to reduce surplus capacity, including reduction in base size, leasing excess base property, or transferring it to another government agency for a variety of alternative uses. The surplus capacity issue also offers an opportunity to DOD to reassess base utilization, to update base requirements with current and future force structure. While BRAC focuses on American military bases, the process and alternatives also have international applications.     

The one‐warehouse multiretailer problem with an order‐up‐to level inventory policy

We consider a two‐level system in which a warehouse manages the inventories of multiple retailers. Each retailer employs an order‐up‐to level inventory policy over T periods and faces an external demand which is dynamic and known. A retailer's inventory should be raised to its maximum limit when replenished. The problem is to jointly decide on replenishment times and quantities of warehouse and retailers so as to minimize the total costs in the system. Unlike the case in the single level lot‐sizing problem, we cannot assume that the initial inventory will be zero without loss of generality. We propose a strong mixed integer program formulation for the problem with zero and nonzero initial inventories at the warehouse. The strong formulation for the zero initial inventory case has only T binary variables and represents the convex hull of the feasible region of the problem when there is only one retailer. Computational results with a state‐of‐the art solver reveal that our formulations are very effective in solving large‐size instances to optimality. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

An economic sequential screening procedure for limited failure populations

An economic sequential screening procedure is considered for limited failure populations in which defective items fail soon after they are put in operation and nondefective ones never fail during the technical life of the items. A cost model is constructed that involves screening test cost and external failure cost. A sequential scheme that minimizes the expected cost is derived from the solution of a dynamic programming formulation and the optimal decision at each stage is obtained in a closed form. © 1994 John Wiley & Sons, Inc.     

The applicability of acceptance sampling with respect to process stability and control

This article examines the applicability of acceptance sampling and the effectiveness of Deming's kp rule in relation to the degree of process stability achieved through statistical process control techniques. A discrete-event simulation model is used to characterize the correlation between the number of defective units in a randomly drawn sample versus in the remainder of a lot, in response to a number of system and control chart parameters. The model reveals that such correlation is typically present when special causes of variation affect the production process from time to time, even though the process is tightly monitored through statistical process control. Comparison of these results to an analogous mixed binomial scenario reveals that the mixed binomial model overstates the correlation in question if the state of the process is not necessarily constant during lot production. A generalization of the kp analysis is presented that incorporates the possibility of dependence between a sample and the unsampled portion of the lot. This analysis demonstrates that acceptance sampling is generally ineffective for lots generated by a process subject to statistical process control, despite the fact that the number of defectives in the sample and in the remainder of the lot are not strictly independent. © 1994 John Wiley & Sons, Inc.     

An exact ceiling point algorithm for general integer linear programming

We present an algorithm called the exact ceiling point algorithm (XCPA) for solving the pure, general integer linear programming problem (P). A recent report by the authors demonstrates that, if the set of feasible integer solutions for (P) is nonempty and bounded, all optimal solutions for (P) are “feasible 1-ceiling points,” roughly, feasible integer solutions lying on or near the boundary of the feasible region for the LP-relaxation associated with (P). Consequently, the XCPA solves (P) by implicitly enumerating only feasible 1-ceiling points, making use of conditional bounds and “double backtracking.” We discuss the results of computational testing on a set of 48 problems taken from the literature.     

Bounds for circular error probabilities

Bounds for P(X + X ⩽ k²σ) are given where X₁ and X₂ are independent normal variables having zero means and variances σ, σ, respectively. This is generalized when X₁ and X₂ are dependent variables with known covariance matrix.     

Optimal sequential replenishment of ships during combat

A carrier battle group is operating in an area where it is subject to attack by enemy aircraft. It is anticipated that air raids will occur in large waves. The uncertain time between raids is available for the replenishment of supplies. We consider the problem of how best to schedule ammunition replenishment during this period. The theory of Gittins indices provides the technical background to the development of a range of models which yield a hierarchy of index-based heuristics for replenishment. One such heuristic is assessed computationally in a more realistic scenario than is explicitly allowed for by the models.     

A replacement model with overhauls and repairs

This article generalizes the classical periodical replacement model with minimal repair by considering the effect of the overhaul, which is assumed to be able to rejuvenate the system. The generalization is based on the notion of the virtual age of a system introduced by Kijima, Morimura, and Suzuki [“Periodical Replacement Problem without Assuming Minimal Repair,” European Journal of Operational Research, 37 , 194–203 (1988)]. © 1995 John Wiley & Sons, Inc.     

Makespan minimization for m parallel identical processors

We introduce an algorithm, called TMO (Two-Machine Optimal Scheduling) which minimizes the makespan for two identical processors. TMO employs lexicographic search in conjunction with the longest-processing time sequence to derive an optimal schedule. For the m identical parallel processors problem, we propose an improvement algorithm, which improves the seed solution obtained by any existing heuristic. The improvement algorithm, called Extended TMO, breaks the original m-machine problem into a set of two-machine problems and solves them repeatedly by the TMO. A simulation study is performed to evaluate the effectiveness of the proposed algorithms by comparing it against three existing heuristics: LPT (Graham, [11]), MULTIFIT (Coffman, Garey, and Johnson, [6]), and RMG (Lee and Massey, [17]). The simulation results show that: for the two processors case, the TMO performs significantly better than LPT, MULTIFIT, and RMG, and it generally takes considerably less CPU time than MULTIFIT and RMG. For the general parallel processors case, the Extended TMO algorithm is shown to be capable of greatly improving any seed solution. © 1995 John Wiley & Sons, Inc.