Aggregating courier deliveries

We consider the problem of efficiently scheduling deliveries by an uncapacitated courier from a central location under online arrivals. We consider both adversary‐controlled and Poisson arrival processes. In the adversarial setting we provide a randomized (3βΔ/2δ ? 1) ‐competitive algorithm, where β is the approximation ratio of the traveling salesman problem, δ is the minimum distance between the central location and any customer, and Δ is the length of the optimal traveling salesman tour overall customer locations and the central location. We provide instances showing that this analysis is tight. We also prove a 1 + 0.271Δ/δ lower‐bound on the competitive ratio of any algorithm in this setting. In the Poisson setting, we relax our assumption of deterministic travel times by assuming that travel times are distributed with a mean equal to the excursion length. We prove that optimal policies in this setting follow a threshold structure and describe this structure. For the half‐line metric space we bound the performance of the randomized algorithm in the Poisson setting, and show through numerical experiments that the performance of the algorithm is often much better than this bound.     

The Damoclean sword of offensive cyber: Policy uncertainty and collective insecurity

Cyberspace is a new domain of operation, with its own characteristics. Cyber weapons differ qualitatively from kinetic ones: They generate effects by non-kinetic means through information, technology, and networks. Their properties, opportunities, and constraints are comparable to the qualitative difference between conventional and nuclear weapons. New weapons and their target sets in a new domain raise a series of unresolved policy challenges at the domestic, bilateral, and international levels about deterrence, attribution, and response. They also introduce new risks: uncertainty about unintended consequences, expectations of efficacy, and uncertainty about both the target’s and the international community’s response. Cyber operations offer considerable benefits for states to achieve strategic objectives both covertly and overtly. However, without a strategic framework to contain and possibly deter their use, make state and non-state behavior more predictable in the absence of reciprocal norms, and limit their impact, an environment where states face persistent attacks that nonetheless fall below the threshold of armed conflict presents a policy dilemma that reinforces collective insecurity.     

Reactor-grade plutonium and nuclear weapons: ending the debate

The claim that reactor-grade plutonium cannot or will not be used to produce nuclear weapons has been used to justify non-nuclear-weapon states’ large stockpiles of plutonium that has been separated from highly radioactive spent fuel. However, by using reduced-mass plutonium cores, it is possible to manufacture reliable nuclear weapons with reactor-grade plutonium. These weapons can have the same design, size, weight, and predetonation probability as weapons using weapon-grade plutonium and would require no special cooling. The increased radiation from reactor-grade plutonium could be easily managed by shielding and operational procedures. Weapons using plutonium routinely produced by pressurized-water reactors could have a lethal area between 40 percent and 75 percent that of weapons using weapon-grade plutonium. In the past, both Sweden and Pakistan considered using reactor-grade plutonium to produce nuclear weapons, and India may be using reactor-grade plutonium in its arsenal today. Despite claims to the contrary, the United States used what was truly reactor-grade plutonium in a successful nuclear test in 1962. The capability of reactor-grade plutonium to produce highly destructive nuclear weapons leads to the conclusion that the separation of plutonium, plutonium stockpiling, and the use of plutonium-based fuels must be phased out and banned.     

Late Medieval Lance Use: Mounted Combat and Martial Arts in Western Europe from the 14th to the 16th Century

Despite the lance’s status and the amount of attention the couched lance has received in historiography, study of its martial art has been neglected. The various lance types and techniques used by western European cavalry have only recently begun to receive scholarly attention. Additionally, Medieval European lance use has too often been studied in isolation, without an adequate understanding of the idiosyncratic and asymmetrical dynamics of mounted combat. Although the charge with the couched lance was a valid tactic, it was only one of many. Light and heavy lances were used in one hand or two to trip, block, unhorse, and wrestle. These techniques were governed by the harsh laws of distance, speed, impact, iron, and asymmetry. By utilizing the surviving Fechtbücher and several Peninsular and Near Eastern sources, a brief foray into the diverse techniques of lance use and their purposes has been attempted here.     

Due-date assignment and early/tardy scheduling on identical parallel machines

This article examines the problem of simultaneously assigning a common due date to a set of independent jobs and scheduling them on identical parallel machines in such a way that the costs associated with the due date and with the earliness or tardiness of the jobs are minimized. We establish that, for certain values of the due-date cost, an optimal schedule for this problem is also optimal for an early/tardy scheduling problem studied by Emmons. We discuss the solution properties for the two problems, and show that both problems are NP-hard even for two machines. We further show that these problems become strongly NP-hard if the number of machines is allowed to be arbitrary. We provide a dynamic programming solution for the problems, the complexity of which indicates that the problems can be solved in pseudopolynomial time as long as the number of machines remains fixed. Finally, we present the results of a limited computational study. © 1994 John Wiley & Sons, Inc.     

Capacitated warehouse location model with risk pooling

In this article, we introduce the capacitated warehouse location model with risk pooling (CLMRP), which captures the interdependence between capacity issues and the inventory management at the warehouses. The CLMRP models a logistics system in which a single plant ships one type of product to a set of retailers, each with an uncertain demand. Warehouses serve as the direct intermediary between the plant and the retailers for the shipment of the product and also retain safety stock to provide appropriate service levels to the retailers. The CLMRP minimizes the sum of the fixed facility location, transportation, and inventory carrying costs. The model simultaneously determines warehouse locations, shipment sizes from the plant to the warehouses, the working inventory, and safety stock levels at the warehouses and the assignment of retailers to the warehouses. The costs at each warehouse exhibit initially economies of scale and then an exponential increase due to the capacity limitations. We show that this problem can be formulated as a nonlinear integer program in which the objective function is neither concave nor convex. A Lagrangian relaxation solution algorithm is proposed. The Lagrangian subproblem is also a nonlinear integer program. An efficient algorithm is developed for the linear relaxation of this subproblem. The Lagrangian relaxation algorithm provides near‐optimal solutions with reasonable computational requirements for large problem instances. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

What you should know about location modeling

Facility location models have been applied to problems in the public and private sectors for years. In this article, the author first presents a taxonomy of location problems based on the underlying space in which the problem is embedded. The article illustrates problems from each part of the taxonomy with an emphasis on discrete location problems. Selected recent research in the area is also discussed. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

Scheduling with tool changes to minimize total completion time: A study of heuristics and their performance

The machine scheduling literature does not consider the issue of tool change. The parallel literature on tool management addresses this issue but assumes that the change is due only to part mix. In practice, however, a tool change is caused most frequently by tool wear. That is why we consider here the problem of scheduling a set of jobs on a single CNC machine where the cutting tool is subject to wear; our objective is to minimize the total completion time. We first describe the problem and discuss its peculiarities. After briefly reviewing available theoretical results, we then go on to provide a mixed 0–1 linear programming model for the exact solution of the problem; this is useful in solving problem instances with up to 20 jobs and has been used in our computational study. As our main contribution, we next propose a number of heuristic algorithms based on simple dispatch rules and generic search. We then discuss the results of a computational study where the performance of the various heuristics is tested; we note that the well‐known SPT rule remains good when the tool change time is small but deteriorates as this time increases and further that the proposed algorithms promise significant improvement over the SPT rule. © 2002 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

Network reliability assessment in a random environment

In this paper we consider networks that consist of components operating under a randomly changing common environment. Our work is motivated by power system networks that are subject to fluctuating weather conditions over time that affect the performance of the network. We develop a general setup for any network that is subject to such environment and present results for network reliability assessment under two repair scenarios. We also present Bayesian analysis of network failure data and illustrate how reliability predictions can be obtained for the network. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 574–591, 2003     

Two‐stage component test plans for testing the reliability of a series system

A system reliability is often evaluated by individual tests of components that constitute the system. These component test plans have advantages over complete system based tests in terms of time and cost. In this paper, we consider the series system with n components, where the lifetime of the i‐th component follows exponential distribution with parameter λ_i. Assuming test costs for the components are different, we develop an efficient algorithm to design a two‐stage component test plan that satisfies the usual probability requirements on the system reliability and in addition minimizes the maximum expected cost. For the case of prior information in the form of upper bounds on λ_i's, we use the genetic algorithm to solve the associated optimization problems which are otherwise difficult to solve using mathematical programming techniques. The two‐stage component test plans are cost effective compared to single‐stage plans developed by Rajgopal and Mazumdar. We demonstrate through several numerical examples that our approach has the potential to reduce the overall testing costs significantly. © 2002 John Wiley & Sons, Inc. Naval Research Logistics, 49: 95–116, 2002; DOI 10.1002/nav.1051