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Proceedings of the 2009 Winter Simulation Conference (WSC)

Date 13-16 Dec. 2009

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Displaying Results 1 - 25 of 309
  • Preface

    Publication Year: 2009, Page(s):1 - 4
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  • The Winter Simulation Conference (WSC)

    Publication Year: 2009, Page(s): 1
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  • WSC Board of Directors

    Publication Year: 2009, Page(s):1 - 2
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  • Conference committee

    Publication Year: 2009, Page(s): 1
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  • WSC'09 track coordinators

    Publication Year: 2009, Page(s):1 - 2
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  • From cracks to climate

    Publication Year: 2009, Page(s):1 - 2
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  • Referees

    Publication Year: 2009, Page(s):1 - 4
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  • Sponsoring societies

    Publication Year: 2009
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  • The WSC Foundation

    Publication Year: 2009, Page(s):1 - 2
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  • Announcement of WSC 2010

    Publication Year: 2009, Page(s):1 - 3
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  • Table of contents

    Publication Year: 2009, Page(s):1 - 22
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  • Simulation for the masses: Spreadsheet-based Monte Carlo simulation

    Publication Year: 2009, Page(s):1 - 11
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (773 KB) | HTML iconHTML

    Spreadsheet-based Monte Carlo simulation has come into relatively widespread use as a methodology supporting studies in risk analysis for a broad range of problem types in areas such as operations management, finance, and marketing. The basic methodology is quite easily assimilated by those familiar with the fundamentals of probability, statistics, and sampling, and the practical applications of t... View full abstract»

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  • Introduction to simulation

    Publication Year: 2009, Page(s):12 - 23
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (871 KB) | HTML iconHTML

    Simulation is experimentation with a model. The behavior of the model imitates some salient aspect of the behavior of the system under study and the user experiments with the model to infer this behavior. This general framework has proven a powerful adjunct to learning, problem solving, and design. In this tutorial, we focus principally on discrete-event simulation-its underlying concepts, structu... View full abstract»

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  • How to build valid and credible simulation models

    Publication Year: 2009, Page(s):24 - 33
    Cited by:  Papers (14)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (399 KB) | HTML iconHTML

    In this tutorial we present techniques for building valid and credible simulation models. Ideas to be discussed include the importance of a definitive problem formulation, discussions with subject-matter experts, interacting with the decision-maker on a regular basis, development of a written assumptions document, structured walk-through of the assumptions document, use of sensitivity analysis to ... View full abstract»

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  • Tips for successful practice of simulation

    Publication Year: 2009, Page(s):34 - 39
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (322 KB) | HTML iconHTML

    A simulation project is much more than building a model. And the skills required go well beyond knowing a particular simulation tool. This paper discusses some important steps to enable project success and some cautions and tips to help avoid common traps. View full abstract»

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  • Representing and generating uncertainty effectively

    Publication Year: 2009, Page(s):40 - 44
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (130 KB) | HTML iconHTML

    Stochastic simulations involve random inputs, so produce random outputs too. This introductory tutorial is meant to call attention to the need to model and generate such inputs in ways that may not be the standard or defaults in simulation-modeling software, yet can be critical to model validity (a.k.a. getting right rather than wrong answers). There are both dangers involved with doing this inapp... View full abstract»

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  • Resampling methods of analysis in simulation studies

    Publication Year: 2009, Page(s):45 - 59
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (971 KB) | HTML iconHTML

    This is an introductory tutorial on the statistical analysis of simulation output, but focusing on the (elementary) use of resampling, and related computer intensive techniques. The aspects covered are (i) input modeling (ii) output analysis (iii) model validation and (iv) model building and selection. The presentation will be very practically oriented including a fair number of real-time spreadsh... View full abstract»

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  • Better than a petaflop: The power of efficient experimental design

    Publication Year: 2009, Page(s):60 - 74
    Cited by:  Papers (7)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (806 KB) | HTML iconHTML

    Recent advances in high-performance computing have pushed computational capabilities to a petaflop (a thousand trillion operations per second) in a single computing cluster. This breakthrough has been hailed as a way to fundamentally change science and engineering by letting people perform experiments that were previously beyond reach. But for those interested in exploring the I/O behavior of thei... View full abstract»

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  • A brief introduction to optimization via simulation

    Publication Year: 2009, Page(s):75 - 85
    Cited by:  Papers (17)  |  Patents (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (485 KB) | HTML iconHTML

    Optimization via simulation (OvS) is an exciting and fast developing area for both research and practice. In this article, we introduce three types of OvS problems: the R&S problems, the continuous OvS problems and the discrete OvS problems, and discuss the issues and current research development for these problems. We also give some suggestions on how to use commercial OvS software in practic... View full abstract»

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  • Agent-based modeling and simulation

    Publication Year: 2009, Page(s):86 - 98
    Cited by:  Papers (34)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (825 KB) | HTML iconHTML

    Agent-based modeling and simulation (ABMS) is a new approach to modeling systems comprised of autonomous, interacting agents. Computational advances have made possible a growing number of agent-based models across a variety of application domains. Applications range from modeling agent behavior in the stock market, supply chains, and consumer markets, to predicting the spread of epidemics, mitigat... View full abstract»

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  • Introduction to financial risk assessment using Monte Carlo simulation

    Publication Year: 2009, Page(s):99 - 118
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1408 KB) | HTML iconHTML

    The fundamental principles of financial risk assessment are discussed, with primary emphasis on using simulation to evaluate and compare alternative investments. First we introduce the key measures of performance for such investments, including net present value, internal rate of return, and modified internal rate of return. Next we discuss types of risk and the key measures of risk, including exp... View full abstract»

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  • Better simulation metamodeling: The why, what, and how of stochastic kriging

    Publication Year: 2009, Page(s):119 - 133
    Cited by:  Papers (20)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (574 KB) | HTML iconHTML

    Stochastic kriging is a methodology recently developed for metamodeling stochastic simulation. Stochastic kriging can partake of the behavior of kriging and of generalized least squares regression. This advanced tutorial explains regression, kriging, and stochastic kriging as metamodeling methodologies, emphasizing the consequences of misspecified models for global metamodeling. It provides an exp... View full abstract»

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  • Input modeling for hospital simulation models using electronic messages

    Publication Year: 2009, Page(s):134 - 147
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (771 KB) | HTML iconHTML

    Health care organizations function in a complex, non-integrated setting, yet the coordination of information, tasks, and equipment across multiple units is essential for productive operations. A variety of simulation models of hospitals exist; however, few reflect resource sharing across multiple departments. Furthermore few models capture the inherent heterogeneity of a hospital's patient mix whi... View full abstract»

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  • Revenue management: Models and methods

    Publication Year: 2009, Page(s):148 - 161
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (379 KB) | HTML iconHTML

    Revenue management is the collection of strategies and tactics firms use to scientifically manage demand for their products and services. The practice has grown from its origins in airlines to its status today as a mainstream business practice in a wide range of industry areas, including hospitality, energy, fashion retail, and manufacturing. This article provides an introduction to this increasin... View full abstract»

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  • Verification and validation of simulation models

    Publication Year: 2009, Page(s):162 - 176
    Cited by:  Papers (19)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (751 KB) | HTML iconHTML

    In this paper we discuss verification and validation of simulation models. Four different approaches to deciding model validity are described; two different paradigms that relate verification and validation to the model development process are presented; various validation techniques are defined; conceptual model validity, model verification, operational validity, and data validity are discussed; ... View full abstract»

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