Inventory competition with yield reliability improvement

This article studies the inventory competition under yield uncertainty. Two firms with random yield compete for substitutable demand: If one firm suffers a stockout, which can be caused by yield failure, its unsatisfied customers may switch to its competitor. We first study the case in which two competing firms decide order quantities based on the exogenous reliability levels. The results from the traditional inventory competition are generalized to the case with yield uncertainty and we find that quantity and reliability can be complementary instruments in the competition. Furthermore, we allow the firms to endogenously improve their yield reliability before competing in quantity. We show that the reliability game is submodular under some assumptions. The results indicate that the competition in quantity can discourage the reliability improvement. With an extensive numerical study, we also demonstrate the robustness of our analytical results in more general settings. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 107–126, 2015     

An economic two-stage screening procedure with a prescribed outgoing quality in logistic and normal models

An economic two-stage screening procedure based on a dichotomous performance variable T and a continuous screening variable X is proposed. X is measured first to decide whether an item should be accepted, rejected, or additional observations should be taken. If no terminal decision is reached, T is then observed to classify the undecided items. Two models are considered; (i) the logistic model, where P(T = 1|X = x) is assumed to be a logistic function of x, and (ii) the normal model, where X given T is assumed to be normally distributed. A simple economic model based on inspection and misclassification costs is constructed. Optimal cutoff values on the screening variable are obtained by minimizing the expected cost subject to the constraint that the average outgoing quality attains a pre-specified level. Solutions are provided for both known-parameter and unknown-parameter cases. © 1995 John Wiley & Sons, Inc.     

Scheduling jobs and maintenance activities on parallel machines

Most machine scheduling models assume that the machines are available all of the time. However, in most realistic situations, machines need to be maintained and hence may become unavailable during certain periods. In this paper, we study the problem of processing a set of n jobs on m parallel machines where each machine must be maintained once during the planning horizon. Our objective is to schedule jobs and maintenance activities so that the total weighted completion time of jobs is minimized. Two cases are studied in this paper. In the first case, there are sufficient resources so that different machines can be maintained simultaneously if necessary. In the second case, only one machine can be maintained at any given time. In this paper, we first show that, even when all jobs have the same weight, both cases of the problem are NP-hard. We then propose branch and bound algorithms based on the column generation approach for solving both cases of the problem. Our algorithms are capable of optimally solving medium sized problems within a reasonable computational time. We note that the general problem where at most j machines, 1 ≤ j ≤ m, can be maintained simultaneously, can be solved similarly by the column generation approach proposed in this paper. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 145–165, 2000     

Strategic capacity decision‐making in a stochastic manufacturing environment using real‐time approximate dynamic programming

In this study, we illustrate a real‐time approximate dynamic programming (RTADP) method for solving multistage capacity decision problems in a stochastic manufacturing environment, by using an exemplary three‐stage manufacturing system with recycle. The system is a moderate size queuing network, which experiences stochastic variations in demand and product yield. The dynamic capacity decision problem is formulated as a Markov decision process (MDP). The proposed RTADP method starts with a set of heuristics and learns a superior quality solution by interacting with the stochastic system via simulation. The curse‐of‐dimensionality associated with DP methods is alleviated by the adoption of several notions including “evolving set of relevant states,” for which the value function table is built and updated, “adaptive action set” for keeping track of attractive action candidates, and “nonparametric k nearest neighbor averager” for value function approximation. The performance of the learned solution is evaluated against (1) an “ideal” solution derived using a mixed integer programming (MIP) formulation, which assumes full knowledge of future realized values of the stochastic variables (2) a myopic heuristic solution, and (3) a sample path based rolling horizon MIP solution. The policy learned through the RTADP method turned out to be superior to polices of 2 and 3. © 2010 Wiley Periodicals, Inc. Naval Research Logistics 2010     

The Regional Economic Effects of Military Base Realignments and Closures

This paper empirically investigates the impact of military base realignments and closures on regional economic activity in light of the 2005 round of Base Realignment and Closure actions. Baseline regressions with county-level data show employment multipliers comparable to those generated from conventional input–output models. However, controlling for possible endogeneity and other regional-specific factors, regressions indicate more tenuous results for spillover effects from the military to the private sector. Only the contractor type of base employment generated economically and statistically meaningful impacts on local employment. In addition, there is strong evidence of asymmetric effects between military buildups and drawdowns.     

Optimal Bayesian single-sampling attribute plans with modified beta prior distribution

In this article we study the properties of the optimal Bayesian single-sampling plans when the prior distribution of the lot fraction defective is modified Beta, which has been found useful in the analysis of inspection schemes for complex production systems. These properties are used to devise an improved and more efficient algorithm for the determination of the optimal sampling plans. Numerical examples are presented to illustrate the potential computational savings of the algorithm.     

Book Reviews

The purpose of this article is to analyse British strategic nuclear targeting between 1974 and 1979, prior to the successful completion of the sophisticated modification to Polaris submarine-missile system codenamed Chevaline. It will use as its starting point the parameters for UK strategic nuclear targeting, and the foundation of the ‘Moscow Criterion’, prior to the deployment of Britain's Polaris submarines which began in 1968. It will then discuss the recommendation by the Chiefs of Staff to retarget Polaris in 1975/76 and the implications of that recommendation in terms of the British approach to strategic nuclear deterrence. The article will conclude with an assessment of these retargeting decisions on the decision to replace Polaris with the US Trident system in 1980.     

A RANDOM RATIONING MECHANISM WHICH REDUCES THE RISKS OF NO SON LEFT AT HOME

This paper empirically re‐examines the long‐run co‐movements and the causal relationships between GDP and defence expenditures in a multivariate model with real defence expenditure per capita (ME), real GDP per capita (GDP), and real capital stock per capita (K). We apply the view of the aggregate production function to construct the empirical model. Using up‐to‐date data for 27 OECD countries and 62 non‐OECD countries for the 1988–2003 period, we combine cross‐sectional and time series data to re‐investigate the relationship between GDP and ME. Previous studies using time series data may have yielded misleading results on account of the short time span of typical datasets. By contrast, we use recently developed panel unit root tests and heterogeneous panel cointegration tests, and conclude that there is fairly strong evidence in favour of the hypothesis of a long‐run equilibrium relationship between GDP and ME. The long‐run panel regression parameter results, such as the fully modified OLS, indicate that a positive relationship between GDP and ME only holds for OECD countries, whereas a negative relationship from ME to GDP only exists in non‐OECD countries under examination and in the panel as a whole. Furthermore, by implementing the dynamic panel‐based error correction model, we determine that GDP and ME lack short‐run causalities, but do show long‐run bidirectional causalities in both OECD and non‐OECD countries.     

THE LONG‐RUN RELATIONSHIP BETWEEN DEFENCE EXPENDITURES AND GDP IN TAIWAN

Using the Solow–Swan growth model and the time‐trend included in the aggregate production function, this study applies the multivariate cointegration approach to re‐investigate the long‐run and causal relationships between defence expenditures and GDP while controlling for capital and labour input in Taiwan during the 1955–2002 period. It examines the long‐run causal relationship using the weak exogeneity test and utilizes general impulse response functions to determine whether a shock to defence expenditures affects economic growth or vice versa. Our findings provide substantive evidence in favour of the existence of a long‐run equilibrium cointegrated relationship between defence expenditures, GDP, labour and capital stock. The results of the weak exogeneity test indicate that a bi‐directional causal relationship exists in the long‐run between defence expenditures and GDP. Thus, the main policy implication that emerges from the long‐run results is that increasing defence expenditures in Taiwan is an effective means to boost overall economic performance and, with this improved economy, it should then be able to increase its defence expenditures further. Lastly, from our dynamic vector error correction model estimations, it is found that defence expenditures are a major means of adjusting for disequilibria that occur within the system.     

9/11: WHAT DID WE KNOW AND WHEN DID WE KNOW IT?

In February 1998, Osama Bin Laden published a signed statement calling for a fatwa against the United States for its having ‘declared war against God’. As we now know, the fatwa resulted in the unprecedented attack of 9/11. The issue of whether or not 9/11 was in any way predictable culminated in the public debate between Richard Clarke, former CIA Director George Tenet and the White House. This paper examines whether there was any evidence of a structural change in the terrorism data at or after February 1998 but prior to June 2001, controlling for the possibility of other breaks in earlier periods. In doing so, we use the standard Bai–Perron procedure and our sequential importance sampling (SIS) Markov Chain Monte Carlo (MCMC) method for identifying an unknown number of breaks at unknown dates. We conclude that sophisticated statistical time‐series analysis would not have predicted 9/11.