Terrorist choice: a stochastic dominance and prospect theory analysis

The paper explores terrorist choice by applying two well-known theoretical frameworks: stochastic dominance and prospect theory (PT). We analyse each pair of attack methods that can be formed from the RAND-MIPT database and the Global Terrorism Database. Instances of stochastic dominance are identified. PT orderings are computed. Attention is accorded to the identification of ‘trigger points’ and the circumstances that may lead to an increased likelihood that a terrorist will select an attack method associated with a higher expected number of fatalities, i.e. a potentially more damaging attack method.     

Military Expenditure,Economic Growth and Heterogeneity

This paper examines the impact of military expenditure on economic growth on a large balanced panel, using an exogenous growth model and dynamic panel data methods for 106 countries over the period 1988–2010. A major focus of the paper is to consider the possibility group heterogeneity and non-linearity. Having estimated the model for all of the countries in the panel and finding that military burden has a negative effect on growth in the short and long run, the panel is broken down into various groupings based upon a range of potentially relevant factors, and the robustness of the results is evaluated. The factors considered are different levels of income, conflict experience, natural resources abundance, openness and aid. The estimates for the different groups are remarkably consistent with those for the whole panel, providing strong support for the argument that military spending has adverse effects on growth. There are, however, some intriguing results that suggest that for certain types of countries military spending has no significant effect on growth.     

Layers of Experiments with Adaptive Combined Design

In the field of nanofabrication, engineers often face unique challenges in resource‐limited experimental budgets, the sensitive nature of process behavior with respect to controllable variables, and highly demanding tolerance requirements. To effectively overcome these challenges, this article proposes a methodology for a sequential design of experiments through batches of experimental runs, aptly named Layers of Experiments with Adaptive Combined Design (LoE/ACD). In higher layers, where process behavior is less understood, experimental regions cover more design space and data points are more spread out. In lower layers, experimental regions are more focused to improve understanding of process sensitivities in a local, data‐rich environment. The experimental design is a combination of a space‐filling and an optimal design with a tuning parameter that is dependent on the amount of information accumulated over the various layers. The proposed LoE/ACD method is applied to optimize a carbon dioxide (epet‐CO2) assisted deposition process for fabricating silver nanoparticles with pressure and temperature variables. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 127–142, 2015     

Single batch machine scheduling with deliveries

We consider the problem of scheduling a set of n jobs on a single batch machine, where several jobs can be processed simultaneously. Each job j has a processing time p_j and a size s_j. All jobs are available for processing at time 0. The batch machine has a capacity D. Several jobs can be batched together and processed simultaneously, provided that the total size of the jobs in the batch does not exceed D. The processing time of a batch is the largest processing time among all jobs in the batch. There is a single vehicle available for delivery of the finished products to the customer, and the vehicle has capacity K. We assume that K = rD, where and r is an integer. The travel time of the vehicle is T; that is, T is the time from the manufacturer to the customer. Our goal is to find a schedule of the jobs and a delivery plan so that the service span is minimized, where the service span is the time that the last job is delivered to the customer. We show that if the jobs have identical sizes, then we can find a schedule and delivery plan in time such that the service span is minimum. If the jobs have identical processing times, then we can find a schedule and delivery plan in time such that the service span is asymptotically at most 11/9 times the optimal service span. When the jobs have arbitrary processing times and arbitrary sizes, then we can find a schedule and delivery plan in time such that the service span is asymptotically at most twice the optimal service span. We also derive upper bounds of the absolute worst‐case ratios in both cases. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 470–482, 2015     

Effects of lethality in naval combat models

In the context of both discrete time salvo models and continuous time Lanchester models we examine the effect on naval combat of lethality: that is, the relative balance between the offensive and defensive attributes of the units involved. We define three distinct levels of lethality and describe the distinguishing features of combat for each level. We discuss the implications of these characteristics for naval decision‐makers; in particular, we show that the usefulness of the intuitive concept “more is better” varies greatly depending on the lethality level. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2004.     

Limiting survival functions of self‐similar structures

We show the existence of a unique analytic single parameter limiting survival function arising from the repeated composition of a coherent structure as the number of components tends to infinity. Examples include the repeated composition process of the bridge structure. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2004.     

Strategies for managing the flexible capacity in the airline industry

The ability to effectively match supply and demand under uncertainty can result in significant revenue benefits in the airline industry. We study the benefits of a Demand Driven Swapping (DDS) approach that takes advantage of the flexibilities in the system and dynamically swaps aircraft as departures near and more accurate demand information is obtained. We analyze the effectiveness of different DDS strategies, characterized by their frequency (how often the swapping decision is revised), in hedging against demand uncertainty. Swapping aircraft several weeks prior to departures will not cause much disturbance to revenue management and operations, but will be based on highly uncertain demands. On the other hand, revising the swapping decision later will decrease the possibility of bad swaps, but at a higher cost of disrupting airport services and operations. Our objective is to provide guidelines on how the flexible (swappable) capacity should be managed in the system. We study analytical models to gain insights into the critical parameters that affect the revenue benefits of the different swapping strategies. Our study determines the conditions under which each of the different DDS strategies is effective. We complement our analysis by testing the proposed DDS strategies on a set of flight legs, using data obtained from United Airlines. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004.