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     

Military Innovation and Tactical Adaptation in the Israel–Hizballah Conflict: The Institutionalization of Lesson-Learning in the IDF

This article highlights a pattern of military adaptation and tactical problem-solving utilized by the Israel Defense Forces (IDF) while engaged in protracted conflict with the Lebanese militant group Hizballah. It discusses the IDF’s recent attempts to institutionalize their historically intuitive process of ad-hoc learning by developing a formal tactical-level mechanism for ‘knowledge management’. The diffusion of this battlefield lesson-learning system that originated at lower-levels of the organization is examined, as well as its implementation and effectiveness during the 2006 Lebanon War. A nuanced analysis of IDF adaptation illustrates the dynamic interplay between both ‘top-down’ and ‘bottom-up’ processes of military innovation.     

Indian Military Modernization and Conventional Deterrence in South Asia

In recent years, headline grabbing increases in the Indian defense budget have raised concerns that India’s on-going military modernization threatens to upset the delicate conventional military balance vis-à-vis Pakistan. Such an eventuality is taken as justification for Islamabad’s pursuit of tactical-nuclear weapons and other actions that have worrisome implications for strategic stability on the subcontinent. This article examines the prospects for Pakistan’s conventional deterrence in the near to medium term, and concludes that it is much better than the pessimists allege. A host of factors, including terrain, the favorable deployment of Pakistani forces, and a lack of strategic surprise in the most likely conflict scenarios, will mitigate whatever advantages India may be gaining through military modernization. Despite a growing technological edge in some areas, Indian policymakers cannot be confident that even a limited resort to military force would achieve a rapid result, which is an essential pre-condition for deterrence failure.     

A sequential scheduling problem with impatient jobs

There are n customers that need to be served. Customer i will only wait in queue for an exponentially distributed time with rate λ_i before departing the system. The service time of customer i has distribution F_i, and on completion of service of customer i a positive reward r_i is earned. There is a single server and the problem is to choose, after each service completion, which currently in queue customer to serve next so as to maximize the expected total return. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 659–663, 2015     

I Will Follow: Smart Power and the Management of Wartime Alliances

Abstract

This paper employs the concept of smart power to construct an analytical framework for assessing wartime alliance management. It makes two arguments. First, wartime sources of soft power differ from those obtaining during peacetime. Second, the coerciveness with which an alliance leader wields hard power towards actual or prospective allies should vary inversely with the amount of soft power it possesses. The smart power framework illuminates three types of alliance management failure. The paper’s key contentions are illustrated with examples furnished from the record of US alliance leadership since World War II.     

Missile Strategy in a Post-Nuclear Age

While the arrival of nuclear weapons coincided roughly with the development of short, medium, intermediate, and eventually intercontinental missiles, the contribution of missile technology to the deterrence equation is often lost. If nuclear weapons were eliminated, even new generation missiles with conventional payloads could struggle to render effective deterrence. But some of the physical and psychological effects commonly ascribed to nuclear weapons could still be in play. And in a world without nuclear weapons, thinking about the use and control of force from the nuclear age would also deserve renewed attention.     

Minimum violations and predictive meta‐rankings for college football

This article presents two meta‐ranking models that minimize or nearly minimize violations of past game results while predicting future game winners as well as or better than leading current systems—a combination never before offered for college football. Key to both is the development and integration of a highly predictive ensemble probability model generated from the analysis of 36 existing college football ranking systems. This ensemble model is used to determine a target ranking that is used in two versions of a hierarchical multiobjective mixed binary integer linear program (MOMBILP). When compared to 75 other systems out‐of‐sample, one MOMBILP was the leading predictive system while getting within 0.64% of the retrodictive optimum; the other MOMBILP minimized violations while achieving a prediction total that was 2.55% lower than the best mark. For bowls, prediction sums were not statistically significantly different from the leading value, while achieving optimum or near‐optimum violation counts. This performance points to these models as potential means of reconciling the contrasting perspectives of predictiveness versus the matching of past performance when it comes to ranking fairness in college football. © 2013 Wiley Periodicals, Inc. Naval Research Logistics 61: 17–33, 2014     

Supply licensing when the manufacturer strategically commits to invest in R&D

This article proposes a strategic reason for a proprietary component supplier to license her technology to a competitor or a manufacturer: her anticipation of the manufacturer's strategic commitment to invest in research and development (R&D). We address this phenomenon with a game theoretic model. Our results show that the manufacturer's full commitment to invest in R&D enables the supplier to license, sell a larger quantity through the supply chain, and charge lower prices. These results are robust to the type of demand uncertainty faced by the manufacturer within the class of increasing generalized failure rate distributions. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 341–350, 2014