Proceedings of the 2011 Winter Simulation Conference (WSC)

11-14 Dec. 2011

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Displaying Results 1 - 25 of 400
  • On innovation, and building and sustaining a successful career in research

    Publication Year: 2011, Page(s):1 - 11
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (228 KB) | HTML iconHTML

    Innovation and the generation of new knowledge are fundamental research goals. As such, proficiency in these areas is essential to becoming a successful researcher. Yet, although a principal goal of graduate school is to train students to become effective researchers, innovation is seldom explicitly discussed. The goal of this article is to fill this gap. Specifically, I provide some insights into... View full abstract»

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  • Annoucement of WSC 2012

    Publication Year: 2011, Page(s):1 - 2
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  • Author directory

    Publication Year: 2011, Page(s):1 - 157
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  • Author index

    Publication Year: 2011, Page(s):1 - 63
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  • Conference Committee

    Publication Year: 2011, Page(s): 1
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  • WSC'11 track coordinators

    Publication Year: 2011, Page(s):1 - 3
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  • WSC board of directors

    Publication Year: 2011, Page(s):1 - 2
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  • The WSC foundation

    Publication Year: 2011, Page(s):1 - 3
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  • Future winter simulation conferences

    Publication Year: 2011, Page(s): 1
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  • Keynote address

    Publication Year: 2011, Page(s):1 - 3
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (218 KB)

    Summary form only given. Provides an abstract for each of the keynote presentations and a brief professional biography of each presenter. View full abstract»

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  • In memoriam: Peter A. W. Lewis (1932–2011)

    Publication Year: 2011, Page(s):1 - 2
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  • Preface

    Publication Year: 2011, Page(s):1 - 5
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  • Referees

    Publication Year: 2011, Page(s):1 - 5
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  • Sponsoring societies

    Publication Year: 2011, Page(s): 1
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  • Table of contents

    Publication Year: 2011, Page(s):1 - 27
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  • Extendsim technology: Scenario management

    Publication Year: 2011, Page(s):12 - 19
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (349 KB) | HTML iconHTML

    Simulation models are typically built to obtain an understanding of the system dynamics and compare alternatives. ExtendSim's Scenario Manager provides an easy interface to evaluate different model configurations and explore the effects of model parameters. Scenario management provides for a systematic, controlled approach to the investigation of a system or process. Among other things, it can be ... View full abstract»

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  • Simulation education - seven reasons for change

    Publication Year: 2011, Page(s):20 - 28
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1222 KB) | HTML iconHTML

    Simulation, once the magic wand of a simulation professional, has the opportunity to become a common tool for analyzing and solving real-world problems in today's fast paced, dynamic environment. Graduating students will have to be prepared to take advantage of that opportunity. Applying simulation today isn't like completing an exercise in a traditional text. Even case studies don't teach student... View full abstract»

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  • Introduction to Simio

    Publication Year: 2011, Page(s):29 - 38
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (865 KB) | HTML iconHTML

    This paper describes the modeling system - Simio™ - that is designed to simplify model building by promoting a modeling paradigm shift from the process orientation to an object orientation. Simio is a simulation modeling framework based on intelligent objects. The intelligent objects are built by modelers and then may be reused in multiple modeling projects. Although the Simio framework is focused... View full abstract»

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  • Automod™ - providing simulation solutions for over 25 years

    Publication Year: 2011, Page(s):39 - 51
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (755 KB) | HTML iconHTML

    Decision making in industry continues to become more complicated. Customers are more demanding, competition is more fierce, and costs for labor and raw materials continue to rise. Managers need state-of-the-art tools to help in planning, design, and operations of their facilities. Simulation provides a virtual factory where ideas can be tested and performance improved. The AutoMod product suite fr... View full abstract»

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  • Recent innovations in Simio

    Publication Year: 2011, Page(s):52 - 62
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2294 KB) | HTML iconHTML

    This paper briefly describes Simio™ simulation software, a simulation modeling framework based on intelligent objects. It then describes a few of the many recent enhancements and innovations including SMORE charts that allow unprecedented insight into your simulation output, sophisticated built-in experimentation that incorporates multi-processor support, optimization, and Risk-based Planning and ... View full abstract»

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  • How the ExpertFit®distribution-fitting software can make your simulation models more valid

    Publication Year: 2011, Page(s):63 - 69
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (200 KB) | HTML iconHTML

    In this paper, we discuss the critical role of simulation input modeling in a successful simulation study. Two pitfalls in simulation input modeling are then presented and we explain how any analyst, regardless of their knowledge of statistics, can easily avoid these pitfalls through the use of the ExpertFit distribution-fitting software. We use a set of real-world data to demonstrate how the soft... View full abstract»

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  • Introduction to SAS Simulation Studio

    Publication Year: 2011, Page(s):70 - 79
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (264 KB) | HTML iconHTML

    An overview is presented of SAS Simulation Studio, an object-oriented, Java-based application for building and analyzing discrete-event simulation models. Emphasis is given to Simulation Studio's hierarchical, entity-based approach to resource modeling, which facilitates the creation of realistic simulation models for systems with complicated resource requirements, such as preemption. Also discuss... View full abstract»

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  • Inside discrete-event simulation software: How it works and why it matters

    Publication Year: 2011, Page(s):80 - 94
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (212 KB) | HTML iconHTML

    This paper provides simulation practitioners and consumers with a grounding in how discrete-event simulation software works. Topics include discrete-event systems; entities, resources, control elements and operations; simulation runs; entity states; entity lists; and entity-list management. The implementation of these generic ideas in AutoMod, SLX, and ExtendSim is described. The paper concludes w... View full abstract»

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  • Monte Carlo estimation of value-at-risk, conditional value-at-risk and their sensitivities

    Publication Year: 2011, Page(s):95 - 107
    Cited by:  Papers (7)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (196 KB) | HTML iconHTML

    Value-at-risk and conditional value at risk are two widely used risk measures, employed in the financial industry for risk management purposes. This tutorial discusses Monte Carlo methods for estimating value-at-risk, conditional value-at-risk and their sensitivities. By relating the mathematical representation of value-at-risk to that of conditional value-at-risk, it provides a unified view of si... View full abstract»

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  • Simulation in statistics

    Publication Year: 2011, Page(s):108 - 119
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (303 KB) | HTML iconHTML

    Simulation has become a standard tool in statistics because it may be the only tool available for analyzing some classes of probabilistic models. We review in this paper simulation tools that have been specifically derived to address statistical challenges and, in particular, recent advances in the areas of adaptive Markov chain Monte Carlo (MCMC) algorithms, and approximate Bayesian calculation (... View full abstract»

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