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Date 9-12 Dec. 2007

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Displaying Results 1 - 25 of 335
  • Preface

    Publication Year: 2007, Page(s):i - iv
    Cited by:  Papers (1)
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    Freely Available from IEEE
  • About the conference

    Publication Year: 2007, Page(s):v - xvii
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  • Author directory

    Publication Year: 2007, Page(s):xviii - lxxiii
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  • WSC 2008 call for papers

    Publication Year: 2007, Page(s):lxxiv - lxxvi
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    Freely Available from IEEE
  • Table of contents

    Publication Year: 2007, Page(s):lxxvii - xcv
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    Freely Available from IEEE
  • Keynote address

    Publication Year: 2007, Page(s): 1
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (165 KB)

    First Page of the Article
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  • Fortieth anniversary special panel: Landmark papers

    Publication Year: 2007, Page(s):2 - 13
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2724 KB) | HTML iconHTML

    To celebrate the fortieth anniversary of the Winter Simulation Conference, we have selected ten landmark papers from the four decades of the conference. In this article, we review these landmark papers and discuss their impact on the theory, education, and practice of simulation. View full abstract»

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  • Fortieth anniversary special panel: Landmark papers

    Publication Year: 2007, Page(s):14 - 25
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2724 KB) | HTML iconHTML

    To celebrate the fortieth anniversary of theWinter Simulation Conference, we have selected ten landmark papers from the four decades of the conference. In this article, we review these landmark papers and discuss their impact on the theory, education, and practice of simulation. View full abstract»

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  • Introduction to simulation

    Publication Year: 2007, Page(s):26 - 37
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (261 KB) | HTML iconHTML

    This is an introductory tutorial on the statistical aspects of computer simulation, and is intended to serve as a springboard to many of the other introductory tutorials that appear elsewhere in the Proceedings. We present a number of motivational examples, followed by material on random number and random variate generation, input analysis of the random variables that drive a simulation, and outpu... View full abstract»

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  • Representing and generating uncertainty effectively

    Publication Year: 2007, Page(s):38 - 42
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (103 KB) | HTML iconHTML

    Stochastic simulations involve at least some random inputs. 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. There are both dangers involved with doing things inappropriately, as well as opportunities to do things better, making for more accurate and more precise res... View full abstract»

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  • The optimizing-simulator: Merging simulation and optimization using approximate dynamic programming

    Publication Year: 2007, Page(s):43 - 53
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (175 KB) | HTML iconHTML

    There is a wide range of simulation problems that involve making decisions during the simulation, where we would like to make the best decisions possible, taking into account not only what we know when we make the decision, but also the impact of the decision on the future. Such problems can be formulated as dynamic programs, stochastic programs and optimal control problems, but these techniques r... View full abstract»

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  • Fundamentals of simulation modeling

    Publication Year: 2007, Page(s):54 - 62
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (217 KB) | HTML iconHTML

    We start with basic terminology and concepts of modeling, and decompose the art of modeling as a process. This overview of the process helps clarify when we should or should not use simulation models. We discuss some common missteps made by many inexperienced modelers, and propose a concrete approach for avoiding those mistakes. After a quick review random number and random variate generation, we ... View full abstract»

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  • Introduction to modeling and generating probabilistic input processes for simulation

    Publication Year: 2007, Page(s):63 - 76
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (659 KB) | HTML iconHTML

    Techniques are presented for modeling and generating the univariate probabilistic input processes that drive many simulation experiments. Emphasis is on the generalized beta distribution family, the Johnson translation system of distributions, and the Bezier distribution family. Also discussed are nonparametric techniques for modeling and simulating time-dependent arrival streams using nonhomogene... View full abstract»

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  • Statistical analysis of simulation output data: The practical state of the art

    Publication Year: 2007, Page(s):77 - 83
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (530 KB) | HTML iconHTML

    One of the most important but neglected aspects of a simulation study is the proper design and analysis of simulation experiments. In this tutorial we give a state- of-the-art presentation of what the practitioner really needs to know to be successful. We will discuss how to choose the simulation run length, the warmup-period duration (if any), and the required number of model replications (each u... View full abstract»

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  • Work smarter, not harder: Guidelines for designing simulation experiments

    Publication Year: 2007, Page(s):84 - 94
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (372 KB) | HTML iconHTML

    We present the basic concepts of experimental design, the types of goals it can address, and why it is such an important and useful tool for simulation. A well-designed experiment allows the analyst to examine many more factors than would otherwise be possible, while providing insights that cannot be gleaned from trial-and-error approaches or by sampling factors one at a time. We focus on experime... View full abstract»

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  • Agent-based modeling and simulation: Desktop ABMS

    Publication Year: 2007, Page(s):95 - 106
    Cited by:  Papers (28)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (947 KB) | HTML iconHTML

    Agent-based modeling and simulation (ABMS) is a new approach to modeling systems comprised of autonomous, interacting agents. ABMS promises to have far-reaching effects on the way that businesses use computers to support decision-making and researchers use electronic laboratories to support their research. Some have gone so far as to contend that ABMS "is a third way of doing science," in addition... View full abstract»

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  • Tips for successful practice of simulation

    Publication Year: 2007, Page(s):107 - 112
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (390 KB) | HTML iconHTML

    Succeeding with a technology as powerful as simulation involves much more than the technical aspects you may have been trained in. The parts of a simulation study that are outside the realm of modeling and analysis can make or break the project. This paper explores the most common pitfalls in performing simulation studies and identifies approaches for avoiding these problems. View full abstract»

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

    Publication Year: 2007, Page(s):113 - 123
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (452 KB) | HTML iconHTML

    This paper provides beginning and intermediate simulation practitioners and interested simulation consumers with a grounding in how discrete-event simulation software works. This is done by describing alternative entity states, the use of lists to organize entities in the various states and the use of algorithms to manage these lists and manipulate entities during a simulation. This general treatm... View full abstract»

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  • Verification and validation of simulation models

    Publication Year: 2007, Page(s):124 - 137
    Cited by:  Papers (38)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (650 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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  • Defense and homeland security applications of multi-agent simulations

    Publication Year: 2007, Page(s):138 - 149
    Cited by:  Papers (9)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3060 KB) | HTML iconHTML

    Department of defense and homeland security analysts are increasingly using multi-agent simulation (MAS) to examine national security issues. This paper summarizes three MAS national security studies conducted at the Naval Postgraduate School. The first example explores equipment and employment options for protecting critical infrastructure. The second case considers non-lethal weapons within the ... View full abstract»

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  • Statistical analysis of simulation output: State of the art

    Publication Year: 2007, Page(s):150 - 161
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (170 KB) | HTML iconHTML

    This paper reviews statistical methods for analyzing output data from computer simulations. Specifically, it focuses on the estimation of steady-state system parameters. The estimation techniques include the replication/deletion approach, the regenerative method, the batch means method, and methods based on standardized time series. View full abstract»

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  • Recent advances in ranking and selection

    Publication Year: 2007, Page(s):162 - 172
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (184 KB) | HTML iconHTML

    This tutorial provides an overview on recent advances made in ranking and selection (R&S) for selecting the best simulated system and discusses challenges that still exist in the field. We focus on indifference-zone R&S procedures that provide a guaranteed probability of correct selection when the best system is at least a user-specified amount better than the other systems. View full abstract»

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  • Real options valuation

    Publication Year: 2007, Page(s):173 - 182
    Cited by:  Papers (1)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (153 KB) | HTML iconHTML

    Managerial flexibility has value. The ability of their managers to make smart decisions in the face of volatile market and technological conditions is essential for firms in any competitive industry. This advanced tutorial describes the use of Monte Carlo simulation and stochastic optimization for the valuation of real options that arise from the abilities of managers to influence the cash flows o... View full abstract»

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  • Regression models and experimental designs: A tutorial for simulation analysts

    Publication Year: 2007, Page(s):183 - 194
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (153 KB) | HTML iconHTML

    This tutorial explains the basics of linear regression metamodels-especially low-order polynomials-and the corresponding statistical designs-namely, fractional factorial designs of resolution III (Plackett-Burman designs), IV (accounting for interactions), V (estimating individual interactions), and central composite designs (CCDs, for second-order polynomial metamodels). This tutorial assumes 'wh... View full abstract»

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  • Making sure you tackle the right problem: Linking hard and soft methods in simulation practice

    Publication Year: 2007, Page(s):195 - 204
    Cited by:  Papers (9)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (515 KB) | HTML iconHTML

    As well as knowledge of computing, statistics and modelling, a successful simulation analyst needs to develop ways to understand the important features of an application domain. The last two decades have seen the increasing use of 'soft' approaches to help analysts structure the problems they are asked to tackle. The idea is to help ensure that the right problem is tackled. The complementary use o... View full abstract»

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