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Introduction to Discrete Event Simulation and Agent-based Modeling

Voting Systems, Health Care, Military, and Manufacturing

  • Textbook
  • © 2011
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Overview

Authors:
  1. Theodore T. Allen

    1. , Industrial and Systems Engineering, The Ohio State University, Columbus, USA

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  • Provides readers with the ability to competently apply technology that is considered key in many industries and branches of government

  • Gives a case study of the author's work on the 2008 USA presidential election process

  • Contains numerous problems and solutions

  • Includes supplementary material: sn.pub/extras

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Table of contents (13 chapters)

  1. Front Matter

    Pages i-xii
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  2. Introduction

    • Theodore T. Allen
    Pages 1-7
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  3. Probability Theory and Monte Carlo

    • Theodore T. Allen
    Pages 9-27
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  4. Input Analysis

    • Theodore T. Allen
    Pages 29-42
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  5. Simulating Waiting Times

    • Theodore T. Allen
    Pages 43-58
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  6. Output Analysis

    • Theodore T. Allen
    Pages 59-77
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  7. Theory of Queues

    • Theodore T. Allen
    Pages 79-86
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  8. Decision Support and Voting Systems Case Study

    • Theodore T. Allen
    Pages 87-110
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  9. Variance Reduction Techniques and Quasi-Monte Carlo

    • Theodore T. Allen
    Pages 111-124
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  10. Simulation Software and Visual Basic

    • Theodore T. Allen
    Pages 125-144
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  11. Introduction to ARENA Software

    • Theodore T. Allen
    Pages 145-160
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  12. Advanced Modeling with ARENA

    • Theodore T. Allen
    Pages 161-174
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  13. Agents and New Directions

    • Theodore T. Allen
    Pages 175-190
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  14. Answers to Odd Problems

    • Theodore T. Allen
    Pages 191-207
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  15. Back Matter

    Pages 209-215
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Keywords

About this book

Discrete event simulation and agent-based modeling are increasingly recognized as critical for diagnosing and solving process issues in complex systems. Introduction to Discrete Event Simulation and Agent-based Modeling covers the techniques needed for success in all phases of simulation projects. These include: • Definition – The reader will learn how to plan a project and communicate using a charter. • Input analysis – The reader will discover how to determine defensible sample sizes for all needed data collections. They will also learn how to fit distributions to that data. • Simulation – The reader will understand how simulation controllers work, the Monte Carlo (MC) theory behind them, modern verification and validation, and ways to speed up simulation using variation reduction techniques and other methods. • Output analysis – The reader will be able to establish simultaneous intervals on key responses and apply selection and ranking, design of experiments (DOE), and black box optimization to develop defensible improvement recommendations. • Decision support – Methods to inspire creative alternatives are presented, including lean production. Also, over one hundred solved problems are provided and two full case studies, including one on voting machines that received international attention. Introduction to Discrete Event Simulation and Agent-based Modeling demonstrates how simulation can facilitate improvements on the job and in local communities. It allows readers to competently apply technology considered key in many industries and branches of government. It is suitable for undergraduate and graduate students, as well as researchers and other professionals.

Reviews

From the reviews:

“The unique feature of Introduction to Discrete Event Simulation and Agent-based Modeling: Voting Systems, Health Care, Military, and Manufacturing is its use of a consistent case study (i.e., voting system) in all chapters, an approach that should help students learn how to conduct a full simulation modelling project. … I have recommended it to students of an undergraduate- and a graduate-level introductory course in computer simulation. … In summary, this text will be suitable for anybody who is seeking a concise introduction to computer simulation.” (Stephan Onggo, Interfaces, Vol. 42 (3), May-June, 2012)

Authors and Affiliations

  • , Industrial and Systems Engineering, The Ohio State University, Columbus, USA

    Theodore T. Allen

About the author

Dr. Theodore Allen is an Associate Professor in Integrated Systems Engineering at The Ohio State University and a co-founder of the software company, Sagata Ltd.  He is a fellow of the American Society of Quality, the winner of several teaching awards, and the recipient of fellowships from Honda and Ford. His previous textbook (2nd edition) is in use at many universities.

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