Optimal arrangement of systems

To location L_i we are to allocate a “generator” and n_i “machines” for i = 1, …,k, where n₁ … n₁ ≧ … ≧ n_k. Although the generators and machines function independently of one another, a machine is operable only if it and the generator at its location are functioning. The problem we consider is that of finding the arrangement or allocation optimizing the number of operable machines. We show that if the objective is to maximize the expected number of operable machines at some future time, then it is best to allocate the best generator and the n₁ best machines to location L₁, the second-best generator and the n₂-next-best machines to location L₂, etc. However, this arrangement is not always stochastically optimal. For the case of two generators we give a necessary and sufficient condition that this arrangement is stochastically best, and illustrate the result with several examples.     

A unifying treatment of replacement policies with minimal repair

This article presents the mathematical background for analyzing maintenance policies with minimal repair. Standard maintenance policies are summarized. A general failure model is introduced which allows a unifying treatment of more recent maintenance policies with minimal repair. In particular, repair cost limit maintenance policies are considered. © 1993 John Wiley & Sons, Inc.     

A probability model for initial crack size and fatigue life of gun barrels

With constant firing, metal fatigue produces cracks in a gun barrel. The useful life of the barrel comes to an end when a crack develops to a critical size. The theory of Fracture Mechanics suggests a formula for crack size growth rate. This formula can be used to determine the life of a barrel, depending on the initial and critical crack sizes and other factors. The initial crack size turns out to be a dominant factor. Unfortunately, accurate measurements are not generally available on the initial crack size. In this paper, we propose a simple probability model for the initial crack size and this, in turn, leads to a probability distribution of the life of the barrel. This last distribution is the well-known exponential distribution with a location shift. The simplicity of this final result is one of the factors that make the model appealing.     

The quay crane scheduling problem with time windows

The quay crane scheduling problem consists of scheduling tasks for loading and unloading containers on cranes that are assigned to a vessel for its service. This article introduces a new approach for quay crane scheduling, where the availability of cranes at a vessel is restricted to certain time windows. The problem is of practical relevance, because container terminal operators frequently redeploy cranes among vessels to speed up the service of high‐priority vessels while serving low‐priority vessels casually. This article provides a mathematical formulation of the problem and a tree‐search‐based heuristic solution method. A computational investigation on a large set of test instances is used to evaluate the performance of the heuristic and to identify the impact of differently structured crane time windows on the achievable vessel handling time. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

Some comments on the optimal assembly problem

It is shown that two recent results of Baxter and Harche [1] on monotone and balanced optimal assemblies hold only under conditions that are more restrictive than those originally proposed by the authors. We describe such additional conditions, illustrate why they are needed, and establish their sufficiency. We also consider a recent result by Malon [11] and demonstrate that, while the result itself is correct, its two proofs were incomplete. A complete proof of an extension of the result is then suggested. © 1995 John Wiley & Sons, Inc.     

India’s nuclear counter-revolution: nuclear learning and the future of deterrence

ABSTRACT

The India–Pakistan near war of February–March 2019 highlights India’s ongoing evolution in strategic thought and practice since its emergence in 1998 as an overt nuclear-weapon possessor. These changes, involving an increasing willingness to engage in the intentional escalation of conflict with a nuclear-armed rival willing to be the first to use nuclear weapons, challenge certain academic assumptions about the behavior of nuclear-weapon states. In particular, they undermine the expectations of the nuclear-revolution theory—which anticipates nuclear and conventional restraint among nuclear-armed rivals through fear of mutual assured destruction—and the model of nuclear learning which underpins this theory, in which new nuclear-weapon states gradually absorb this restraint through policy-maker learning. This article explores how India’s learning pathway since 1998 has deviated from these expectations. India is instead pursuing its own “revolution,” in the direction of creating capabilities for flexible response and escalation dominance. It concludes by illuminating the similarities between Indian strategic behavior and contemporary practices of other nuclear-armed states, and suggests that New Delhi’s emerging de facto nuclear doctrine and posture is part of a broader empirical challenge to our current conceptions of the nuclear revolution and of nuclear learning.     

Optimal inventory and dynamic admission policies for a retailer of seasonal products with affiliate programs and drop‐shipping

This article investigates the optimal inventory and admission policies for a “Clicks‐and‐Bricks” retailer of seasonal products that, in addition to selling through its own physical and online stores, also sells through third‐party websites by means of affiliate programs. Through postings on partners' webpages, an affiliate program allows a retailer to attract customers who would otherwise be missed. However, this retailer needs to pay a commission for each sale that originates from the website operators participating in the program. The retailer may also refer online orders to other sources (such as distributors and manufacturers) for fulfillment through a drop‐shipping agreement and thus earns commissions. This would be an option when, for example, the inventories at the physical stores were running low. Therefore, during the selling horizon, the retailer needs to dynamically control the opening/closing of affiliate programs and decide on the fulfillment option for online orders. On the basis of a discrete‐time dynamic programming model, the optimal admission policy of the retailer is investigated in this paper, and the structural properties of the revenue function are characterized. Numerical examples are given to show the revenue impact of optimal admission control. The optimal initial stocking decisions at the physical stores are also studied. © 2009 Wiley Periodicals, Inc. Naval Research Logistics 2009     

Inventory policies for a make‐to‐order system with a perishable component and fixed ordering cost

We consider a make‐to‐order production system where two major components, one nonperishable (referred to as part 1) and one perishable (part 2), are needed to fulfill a customer order. In each period, replenishment decisions for both parts need to be made jointly before demand is realized and a fixed ordering cost is incurred for the nonperishable part. We show that a simple (s_n,S,S) policy is optimal. Under this policy, S along with the number of backorders at the beginning of a period if any and the availability of the nonperishable part (part 1) determines the optimal order quantity of the perishable part (part 2), while (s_n,S) guide when and how much of part 1 to order at each state. Numerical study demonstrates that the benefits of using the joint replenishment policy can be substantial, especially when the unit costs are high and/or the profit margin is low. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009