Modeling and Visualization of Complex Systems and Enterprises

William B. Rouse, PhD., is the Alexander Crombie Humphreys Chair of Economics in Engineering at Stevens Institute of Technology, and Director of the university wide Center for Complex Systems and Enterprises. He is also Professor Emeritus of Industrial and Systems Engineering at the Georgia Institute of Technology. He is a member of the National Academy of Engineering.

• Preface xi1 Introduction and Overview 1Systems Perspectives 2Systems Movement 3Philosophical Background 3Seminal Concepts – Systems Science 5Seminal Concepts – Economics/Cognition 6Seminal Concepts – Operations Research 7Seminal Concepts – Sociology 8Complexity and Complex Systems 8Complex Versus Complicated Systems 11Systems Practice 13Phenomena as the Starting Point 19Oveview of Book 20Chapter 1: Introduction and Overview 20Chapter 2: Overall Methodology 21Chapter 3: Perspectives on Phenomena 21Chapter 4: Physical Phenomena 21Chapter 5: Human Phenomena 21Chapter 6: Economic Phenomena 22Chapter 7: Social Phenomena 22Chapter 8: Visualization of Phenomena 22Chapter 9: Computational Methods and Tools 23Chapter 10: Perspectives on Problem Solving 23References 232 Overall Methodology 27Introduction 27Problem Archetypes 29Deterring or Identifying Counterfeit Parts 29Financial Systems and Bursting Bubbles 30Human Responses and Urban Resilience 30Traffic Control via Congestion Pricing 31Impacts of Investments in Healthcare Delivery 31Human Biology and Cancer 31Comparison of Problems 32Methodology 33Summary 35An Example 36Supporting the Methodology 40Conclusions 41References 413 Perspectives on Phenomena 43Introduction 43Definitions 43Historical Perspectives 46Steam to Steamboats 46Wind to Wings 47Electricity to Electric Lights 47Macro and Micro Physics 47Probability and Utility 48Contemporary Perspectives 48Four Fundamental Forces 48Computational Fluid Dynamics 49Integrated Circuit Design 49Supply Chain Management 50Summary 50Taxonomy of Phenomena 50Behavioral and Social Systems 52Problems versus Phenomena 54Visualizing Phenomena 54Conclusions 58References 594 Physical Phenomena 61Introduction 61Natural Phenomena 61Example – Human Biology 64Example – Urban Oceanography 67Designed Phenomena 69Example – Vehicle Powertrain 73Example – Manufacturing Processes 75Deterring or Identifying Counterfeit Parts 76Conclusions 80References 805 Human Phenomena 83Descriptive Versus Prescriptive Approaches 84Models of Human Behavior and Performance 86Example – Manual Control 87Example – Problem Solving 89Example – Multitask Decision Making 90Traffic Control Via Congestion Pricing 92Mental Models 95Team Mental Models 99Performing Arts Teams 101Fundamental Limits 104Conclusions 107References 1076 Economic Phenomena 111Introduction 111Microeconomics 113Theory of the Firm 113Theory of the Market 114Example – Optimal Pricing 114Example – Investing in People 118Summary 119Macroeconomics 119Tax Rates Interest Rates and Inflation 120Macroeconomic Models 126Summary 128Behavioral Economics 128Prospect Theory 131Risk Perception 132Attribution Errors 133Management Decision Making 134Human Intuition 135Intuition versus Analysis 136Summary 137Economics of Healthcare Delivery 137Conclusions 139References 1407 Social Phenomena 143Introduction 143Emergent versus Designed Organizational Phenomena 143Direct versus Representative Political Phenomena 144Modeling Complex Social Systems 145Example – Earth as a System 145Physics-Based Formulations 149Example – Castes and Outcastes 151Network Theory 158Game Theory 162Example – Acquisition as a Game 165Simulation 168Example – Port and Airport Evacuation 170Example – Emergence of Cities 171Urban Resilience 172A Framework for Urban Resilience 173Summary 176Conclusions 176References 1768 Visualization of Phenomena 179Introduction 179Human Vision as a Phenomenon 180Basics of Visualization 180Example – Space Shuttle Challenger 181Purposes of Visualizations 183Examples – Co-Citation Networks and Mobile Devices 184Design Methodology 185Use Case Illustrations 186Example – Big Graphics and Little Screens 190Visualization Tools 193Data 195Structure 195Dynamics 195Immersion Lab 196Policy Flight Simulators 198Background 198Multilevel Modeling 199Example – Employee Prevention and Wellness 200People’s Use of Simulators 203Conclusions 205References 2069 Computational Methods and Tools 209Introduction 209Modeling Paradigms 210Dynamic Systems Theory 212Control Theory 214Estimation Theory 216Queuing Theory 217Network Theory 218Decision Theory 221Problem-Solving Theory 224Finance Theory 225Summary 228Levels of Modeling 228Representation to Computation 230Dynamic Systems 230Discrete-Event Systems 231Agent-Based Systems 231Optimization-Based Frame 231Summary 233Model Composition 233Entangled States 233Consistency of Assumptions 235Observations 236Computational Tools 236Conclusions 237References 23810 Perspectives on Problem Solving 241Introduction 241What is? Versus What if? 242Case Studies 243Business Planning 243New Product Planning 245Technology Investments 248Enterprise Transformation 250Observations on Problem Solving 253Starting Assumptions 253Framing Problems 253Implementing Solutions 255Research Issues 255Decomposition 256Mapping 256Scaling 257Approximation 257Identification 257Parameterization 258Propagation 258Visualization 259Curation 259Conclusions 259References 261Index 263

"The book is written for graduate students studying systems science and engineering and professionals involved in systems science and engineering, those involved in complex systems such as healthcare delivery, urban systems, sustainable energy, financial systems, and national security." (Zentralblatt MATH, 2016)