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Introduces various modeling and simulation methods and paradigms that are used to explain and solve the predominant challenges facing society

Handbook of Real-World Applications in Modeling and Simulation provides a thorough explanation of modeling and simulation in the most useful, current, and predominant applied areas of transportation, homeland security, medicine, operational research, military science, and business modeling. Offering a cutting-edge and accessible presentation, this book discusses how and why the presented domains have become leading applications of modeling and simulation techniques.

Contributions from leading academics and researchers integrate modeling and simulation theories, methods, and data to analyze challenges that involve technological and social issues. The book begins with an introduction that explains why modeling and simulation is a reliable analysis assessment tool for complex systems problems. Subsequent chapters provide an orientation to various modeling and simulation methods and paradigms that are used to explain and solve the predominant challenges across real-world applied domains. Additionally, the handbook:

Provides a practical one-stop reference on modeling and simulation and contains an accessible introduction to key concepts and techniques

Introduces, trains, and prepares readers from statistics, mathematics, engineering, computer science, economics, and business to use modeling and simulation in their studies and research

Features case studies that are representative of fundamental areas of multidisciplinary studies and provides a concise look at the key concepts of modeling and simulation

Contains a collection of original ideas on modeling and simulation to help academics and practitioners develop a multifunctional perspective

Self-contained chapters offer a comprehensive approach to explaining each respective domain and include sections that explore the related history, theory, modeling paradigms, and case studies. Key terms and techniques are clearly outlined, and exercise sets allow readers to test their comprehension of the presented material.

Handbook of Real-World Applications in Modeling and Simulation is an essential reference for academics and practitioners in the areas of operations research, business, management science, engineering, statistics, mathematics, and computer science. The handbook is also a suitable supplement for courses on modeling and simulation at the graduate level.




Table of contents

Contributors xiii

Preface xvii

Introduction 1

1 Research and Analysis for Real-World Applications 8
Catherine M. Banks

1.1 Introduction and Learning Objectives 8

1.1.1 Learning Objectives 10

1.2 Background 10

1.3 M&S Theory and Toolbox 13

1.3.1 Simulation Paradigms 15

1.3.2 Types of Modeling 16

1.3.3 Modeling Applications 17

1.4 Research and Analysis Methodologies 18

Case Study: A Methodology for M&S Project Progression 20

Summary 23

Key Terms 24

Exercises 25

References 25

2 Human Behavior Modeling: A Real-World Application 26
John A. Sokolowski

2.1 Introduction and Learning Objectives 26

2.2 Background and Theory 27

2.2.1 Classical Decision Theory 27

2.2.2 Naturalistic Decision Making 31

2.2.3 Recognition-Primed Decision Model 33

2.2.4 Military Decision Making 37

2.2.5 Computational Techniques for Implementing the CJTF Decision Process 40

2.2.6 Summary of the State-of-the-Art 53

Case Studies 54

Summary 81

Key Terms 82

Exercises 83

References 83

Appendix: A Decision Scenario and Associated Data 88

3 Transportation 93
R. Michael Robinson

3.1 Introduction and Learning Objectives 93

3.2 Background 94

3.3 Theory 95

3.3.1 Simulation Levels 95

3.3.2 Traffic Analysis Zones 97

3.3.3 The Four-Step Model 98

3.3.4 Method of Successive Averages 102

3.3.5 Volume Delay Functions 105

3.3.6 Dynamic Traffic Assignment 108

3.4 Transportation Modeling Applications 113

3.4.1 Traffic Demand Models 113

3.4.2 Public Transportation Models 114

3.4.3 Freight Modeling 117

3.4.4 Evacuation Simulations 121

Summary 124

Key Terms 125

Exercises 126

References 126

Further Reading 127

4 Homeland Security Risk Modeling 129
Barry C. Ezell

4.1 Introduction and Learning Objectives 129

4.2 Background 131

4.2.1 Bioterrorism Risk Assessment 2006 132

4.2.2 Estimating Likelihood of Terrorist Events 133

4.2.3 Risk Assessed as a Function of Threat Vulnerability and Consequence 135

4.3 Theory and Applications in Risk Modeling 136

4.3.1 Philosophical Considerations 137

4.3.2 Ontology and Epistemology 138

4.3.3 Issues and Implications for the Risk Analyst 138

4.3.4 Philosophical Considerations Summary 141

4.3.5 System Principals and Applications for the Risk Analyst 142

4.3.6 Factors in Developing a Risk Assessment Study Plan 143

4.3.7 Scope and Bound in a Risk Study: Constraints Limitations and Assumptions 145

4.3.8 Well-Known Challenge in Homeland Security Studies 146

4.4 Elements of a Study Plan 147

4.5 Modeling Paradigms 148

4.5.1 Simple Verses Complex Methodologies 148

4.5.2 Quantitative and Qualitative Designs 148

4.5.3 Modeling Approaches and Examples 150

4.5.4 Verification and Validation for Risk Models 156

Case Studies 157

Summary 161

Key Terms 161

Exercises 161

References 162

Further Reading 164

5 Operations Research 165
Andrew J. Collins and Christine S.M. Currie

5.1 Introduction and Learning Objectives 165

5.2 Background 166

5.2.1 OR Techniques 168

5.3 Theory 169

5.3.1 Problem Structuring Methods 169

5.3.2 Queuing Theory 175

5.3.3 Decision Analysis 179

5.3.4 Game Theory 182

5.3.5 Optimization 186

5.4 Modeling Paradigms 192

Case Studies 193

Summary 199

Key Terms 201

Exercises 202

x Contents

References 204

Further Reading 206

6 Business Process Modeling 207
Rafael Diaz Joshua G. Behr and Mandar Tulpule

6.1 Introduction and Learning Objectives 207

6.2 Background 207

6.3 Discrete-Event Simulation 214

6.3.1 Introduction 214

6.3.2 Fundamentals 215

6.3.3 Queuing System Model Components 218

6.3.4 Time Advance Mechanism 219

6.3.5 Simulation Flowchart 220

6.4 Discrete-Event Simulation Case Study 221

6.4.1 Introduction 222

6.4.2 Background 222

6.4.3 Research Question 223

6.4.4 Overview of Optimization Model 224

6.4.5 The Simulation Model 225

6.4.6 Experimental Setting 225

6.4.7 Simulation Parameterization and Execution 226

6.4.8 Weigh Zones and Product Reassignment 226

6.4.9 Results 226

6.5 System Dynamics Simulation 227

6.5.1 Introduction 227

6.5.2 Fundamentals 228

6.5.3 The Stock and Flow Diagrams 229

6.5.4 Model Calibration 231