ZERO NUCLEAR WEAPONS

The current nuclear nonproliferation order is no longer sustainable. The Treaty on the Non-Proliferation of Nuclear Weapons (NPT) has weakened considerably over the years, with nuclear have-nots displaying increased dissatisfaction with the status quo. Meanwhile, demands for civilian nuclear technology have led to increased proliferation risks in the form of dual-use technologies. Arms control as we currently understand it—piecemeal treaties and agreements—is no longer sufficient to address the growing threat of proliferation and the frailty of the NPT. This article calls for a bolder nonproliferation agenda pursuing multilateral nuclear disarmament. Disarmament is, in fact, technologically achievable; a lack of political will stands as the only remaining roadblock to a world free of nuclear weapons. A better understanding of the technological feasibility of disarmament, as well as recognition of the diminishing strategic value of nuclear weapons, will help to erode this political reluctance.     

Properties of some stochastic orders: A unified study

The notions of the likelihood ratio order of degree s (s ≥ 0) are introduced for both continuous and discrete integer‐valued random variables. The new orders for s = 0, 1, and 2 correspond to the likelihood ratio, hazard rate, and mean residual life orders. We obtain some basic properties of the new orders and their up shifted stochastic orders, and derive some closure properties of them. Such a study is meaningful because it throws an important light on the understanding of the properties of the likelihood ratio, hazard rate, and mean residual life orders. On the other hand, the properties of the new orders have potential applications. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2004.     

Group testing procedures with quantitative features and incomplete identification

We present a group testing model for items characterized by marker random variables. An item is defined to be good (defective) if its marker is below (above) a given threshold. The items can be tested in groups; the goal is to obtain a prespecified number of good items by testing them in optimally sized groups. Besides this group size, the controller has to select a threshold value for the group marker sums, and the target number of groups which by the tests are classified to consist only of good items. These decision variables have to be chosen so as to minimize a cost function, which is a linear combination of the expected number of group tests and an expected penalty for missing the desired number of good items, subject to constraints on the probabilities of misclassifications. We treat two models of this kind: the first one is based on an infinite population size, whereas the second one deals with the case of a finite number of available items. All performance measures are derived in closed form; approximations are also given. Furthermore, we prove monotonicity properties of the components of the objective function and of the constraints. In several examples, we study (i) the dependence of the cost function on the decision variables and (ii) the dependence of the optimal values of the decision variables (group size, group marker threshold, and stopping rule for groups classified as clean) and of the target functionals (optimal expected number of tests, optimal expected penalty, and minimal expected cost) on the system parameters.© 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

Double Mover–Stayer model on customer switching in telecommunications industry

Customer acquisition and customer retention are the most important challenges in the increasingly competitive telecommunications industry. Traditional studies of customer switching always assume that customers are homogeneous, and thus that model customer switching behavior follows a Markov formulation. However, this postulation is obviously inappropriate in most instances. Blumen et al. (Cornell Studies of Industrial and Labor Relations, Cornell University Press, Ithaca, NY, 1955) developed the Mover–Stayer (MS) model, a generalization of the Markov chain model, to relax the requirement of homogeneity and allow the presence of heterogeneity with two different types of individuals—“stayers,” who purchase the same kinds of products or services throughout the entire observation period; and “movers,” who look for variety in products or services over time. There are two purpose of this article. First, we extend the MS model to a Double Mover‐Stayer (DMS) model by assuming the existence of three types of individuals in the market: (1) stable and loyal customers, who have stable usage within the same company; (2) instable but loyal customers, whose usage varies within the same company over time; and (3) disloyal customers, who switch from one company to another to seek for new experiences or/and benefits. We also propose an estimation method for the DMS model. Second, we apply the DMS model to telecommunications data and demonstrate how it can be used for pattern identification, hidden knowledge discovery, and decision making. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

Mitigation of the blast load effects on a building structure using newly composite structural configurations

In this study, a nonlinear three-dimensional hydrocode numerical simulation was carried out using AUTODYN-3D to investigate the effect of blasting of a high explosive material (TNT) against several configurations of the composite structure. Several numerical models were carried out to study the effect of varying the thickness of the walls and the effect of adding an air layer or aluminum foam layer inside two layers of concrete in mitigating the effect of blast waves on the structure walls. The results showed that increasing the thickness of walls has a good effect on mitigating the effect of blast waves. When a layer of air was added, the effect of blast waves was exaggerated, while when a layer of aluminum foam was added the blast wave effects were mitigated with a reasonable percentage.     

On‐line algorithms for minimizing makespan on batch processing machines

We consider problem of scheduling jobs on‐line on batch processing machines with dynamic job arrivals to minimize makespan. A batch machine can handle up to B jobs simultaneously. The jobs that are processed together from a batch, and all jobs in a batch start and complete at the same time. The processing time of a batch is given by the longest processing time of any job in the batch. Each job becomes available at its arrival time, which is unknown in advance, and its processing time becomes known upon its arrival. In the first part of this paper, we address the single batch processing machine scheduling problem. First we deal with two variants: the unbounded model where B is sufficiently large and the bounded model where jobs have two distinct arrival times. For both variants, we provide on‐line algorithms with worst‐case ratio (the inverse of the Golden ratio) and prove that these results are the best possible. Furthermore, we generalize our algorithms to the general case and show a worst‐case ratio of 2. We then consider the unbounded case for parallel batch processing machine scheduling. Lower bound are given, and two on‐line algorithms are presented. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 241–258, 2001     

Short-term retrenchment planning in hierarchical manpower systems

We address the issue of short-term retrenchment planning required of organizations that are phasing down their manpower levels at rates faster than are allowed by natural attrition. Specifically, the problem we study is as follows: given the initial and target grade populations in a hierarchical manpower system at the end of a finite time horizon and the per-period rate of natural attrition for each grade, find a stationary manpower policy that minimizes the maximum per-period rate of retrenchment across all the grades over all stationary policies that yield the target grade populations at the end of the horizon. Because the problem is a nonconvex, nonseparable, nonlinear program, we develop a heuristic in which the promotion proportions of all the grades are successively fixed, starting from the lowest grade. We prove optimality of the heuristic policy in three nontrivial situations. In a computational experiment, in 135 out of 150 randomly generated instances (i.e., in 90% of the cases), the heuristic yielded a solution that was as good or better than that yielded by a benchmark computer program that solves the present problem as a nonlinear program. Further, the average computational time under the heuristic was an order of magnitude less than that under the program. © 1995 John Wiley & Sons, Inc.     

A suboptimality bound for permutation policies in single machine stochastic scheduling

A general class of single machine stochastic scheduling problems incorporating precedence constraints is modelled as a family of competing Markov decision processes. A bound on the optimal return yields a suboptimality bound for permutation policies. This in turn leads to a generalised “used better than new” principle as a (highly intuitive) sufficient condition for the optimality of a permutation policy in the class of all (preemptive) policies. © 1995 John Wiley & Sons, Inc.     

The impact of exponential smoothing forecasts on the bullwhip effect

An important phenomenon often observed in supply chain management, known as the bullwhip effect, implies that demand variability increases as one moves up the supply chain, i.e., as one moves away from customer demand. In this paper we quantify this effect for simple, two‐stage, supply chains consisting of a single retailer and a single manufacturer. We demonstrate that the use of an exponential smoothing forecast by the retailer can cause the bullwhip effect and contrast these results with the increase in variability due to the use of a moving average forecast. We consider two types of demand processes, a correlated demand process and a demand process with a linear trend. We then discuss several important managerial insights that can be drawn from this research. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 269–286, 2000     

Explicit modeling of detection within a stochastic duel

Many mathematical models have been formulated to describe combat between two weapon systems. However, until recently duel models did not explicitly represent target detection within a duel, leading to the necessity for the development of new model for each tactical situation. An earlier article by two of the authors described a duel between weapons with constant firing times and explicit modeling of detection. This article enhances the study of this form of duel between weapons by introducing a variable parameter for firing times. This enhancement removes the discontinuities evident during parametric analysis of the earlier model and hence provides a more coherent model of this combat situation. © 1993 John Wiley & Sons, Inc.