113 research outputs found

    Cramer-von Mises Variance Estimators for Simulations

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    Proceedings of the 1991 Winter Simulation Conference Barry L. Nelson, W. David Kelton, Gordon M. Clark (eds.)We study estimators for the variance parameter u 2 of a stationary process. The estimators are based on weighted Cramer-van Mises statistics formed from the standardized time series of the process. Certain weightings yield estimators which are "first-order unbiased" for u2 and which have low variance. We also show how the Cramer-von Mises estimators are related to the standardized time series area estimator; we use this relationship to establish additional estimators for u2

    Modelling human network behaviour using simulation and optimization tools: the need for hybridization

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    The inclusion of stakeholder behaviour in Operations Research / Industrial Engineering (OR/IE) models has gained much attention in recent years. Behavioural and cognitive traits of people and groups have been integrated in simulation models (mainly through agent-based approaches) as well as in optimization algorithms. However, especially the influence of relations between different actors in human networks is a broad and interdisciplinary topic that has not yet been fully investigated. This paper analyses, from an OR/IE point of view, the existing literature on behaviour-related factors in human networks. This review covers different application fields, including: supply chain management, public policies in emergency situations, and Internet-based human networks. The review reveals that the methodological approach of choice (either simulation or optimization) is highly dependent on the application area. However, an integrated approach combining simulation and optimization is rarely used. Thus, the paper proposes the hybridization of simulation with optimization as one of the best strategies to incorporate human behaviour in human networks and the resulting uncertainty, randomness, and dynamism in related OR/IE models.Peer Reviewe

    Reactive strategies for containing developing outbreaks of pandemic influenza

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    Abstract Background In 2009 and the early part of 2010, the northern hemisphere had to cope with the first waves of the new influenza A (H1N1) pandemic. Despite high-profile vaccination campaigns in many countries, delays in administration of vaccination programs were common, and high vaccination coverage levels were not achieved. This experience suggests the need to explore the epidemiological and economic effectiveness of additional, reactive strategies for combating pandemic influenza. Methods We use a stochastic model of pandemic influenza to investigate realistic strategies that can be used in reaction to developing outbreaks. The model is calibrated to documented illness attack rates and basic reproductive number (R0) estimates, and constructed to represent a typical mid-sized North American city. Results Our model predicts an average illness attack rate of 34.1% in the absence of intervention, with total costs associated with morbidity and mortality of US81millionforsuchacity.Attackratesandeconomiccostscanbereducedto5.481 million for such a city. Attack rates and economic costs can be reduced to 5.4% and US37 million, respectively, when low-coverage reactive vaccination and limited antiviral use are combined with practical, minimally disruptive social distancing strategies, including short-term, as-needed closure of individual schools, even when vaccine supply-chain-related delays occur. Results improve with increasing vaccination coverage and higher vaccine efficacy. Conclusions Such combination strategies can be substantially more effective than vaccination alone from epidemiological and economic standpoints, and warrant strong consideration by public health authorities when reacting to future outbreaks of pandemic influenza

    Simulation of Transportation Logistics

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    Proceedings of the 2002 Winter Simulation Conference E. Yücesan, C.-H. Chen, J. L. Snowdon, and J. M. Charnes, eds.In this paper, we discuss issues concerning the simulation of transportation systems. In particular, we demonstrate a number of implementation tricks that are designed to make the modeling and coding processes more efficient and transparent. We present examples involving the simulation of commercial airline and military sealift operations

    Cramer-Von Mises Variance Estimators for Simulations

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    We study estimators for the variance parameter sigma(2) of a stationary process. The estimators are based on weightings yield estimators that are 'first-order unbiased' for sigma (2) We derive an expression for the asymptotic variance of the new estimators; this expression is then used to obtain the first-order unbiased estimator having the smallest variance among fixed-degree polynomial weighting functions. Although our work is based on asymptotic theory, we present exact and empirical examples to demonstrate the new estimators' small-sample robustness.Naval Postgraduate School, Monterey, California.http://archive.org/details/cramervonmisesva00goldO&MN direct fundingApproved for public release; distribution is unlimited

    An Investigation of Finite Sample Behavior of Confidence Interval Estimation Procedures in Computer Simulation

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    Investigated are the small sample behavior and convergence properties of confidence interval estimators (CIE's) for the mean of a stationary discrete process. We consider CIE's arising from nonoverlapping batch means, overlapping batch means, and standardized time series, all of which are commonly used in discrete-event simulation. For a specific CIE, the performance measures of interest include the coverage probability, and the expected value and variance of the half-length. We use both empirical and analytical methods to make detailed comparisons regarding the behavior of the CIE's for a variety of stochastic processes. All of the CIE's under study are asymptotically valid; however, they are usually invalid for small sample sizes. We find that for small samples, the bias of the variance parameter estimator figures significantly in CIE coverage performance-the less bias the better. A Secondary role is played by the Marginal distribution of the stationary process. Not all CIE's are equal - some require fewer observations before manifesting the properties for CIE validityNaval Postgraduate School, Monterey, California.http://archive.org/details/investigationoff00sargO&MN Direct FundingNAApproved for public release; distribution is unlimited

    Agent-based simulations using human performance models for national airspace system risk assessment

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    Issued as final reportUnited States. National Aeronautics and Space Administratio

    Choosing the best simulated system with applications to manufacturing

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    Issued as Annual report, and Final project report, Project no. E-24-623Includes bibliographical references [leaves 19-22].Interim report and Final report have co-author: David Goldsman
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