A hands-on approach to understanding, designing, analyzing, and evaluating complex systems During the last few years, Simulation-Based Systems Engineering (SBSE) has become an essential tool for the design and evaluation of complex systems. This is the first book to cover the basic principles of complex systems through the use of hands-on experimentation using an icon-based simulation tool. Utilizing the accompanying software tool ExtendSim, which works with the OpEMCSS library, readers are invited to engage in simulation-based experiments that demonstrate the principles of complex systems with an emphasis on design, analysis, and evaluation. A number of real-world examples are included to demonstrate how to model complex systems across a range of engineering, business, societal, economic, and scientific disciplines. Beginning with an introduction to SBSE, the book covers: Simulation concepts and building blocks Systems design and model development Markov model development Reliability processes Queuing theory in SBSE Rule-based learning and adaptation Agent motion and spatial interactions Multi-agent system of systems Assuming only a very basic background in problem-solving ability, this book is ideal as a textbook for students (a homework solution manual is also available) and as a reference book for practitioners in industry.

Table of Contents:
Preface xiii Acknowledgments xvii Overview xix 1 Introduction to Simulation-Based Systems Engineering 1 1.1 Definition of Complex Systems 3 1.1.1 Exercise: Model a Goal-Oriented Activity 6 1.1.2 Agent-Based System Architectures 9 1.1.3 Simulation and AI-Based System Design 11 1.1.4 Expansionism Versus Reductionism 12 1.1.5 Summary 15 1.2 Using Simulation to Understand Complex Systems 15 1.2.1 ExtendSim Discrete-Event Simulation User Environment and OpEMCSS Overview 15 1.2.2 Simulation Model Development Procedure 17 1.2.3 Simulation Programs: How Serial and Parallel Process Models Work 21 1.2.4 Sensitivity Analysis 29 1.3 Bringing Complex Systems into Being 30 1.3.1 Definition of Systems Engineering 31 1.3.2 Levels of System Description 33 1.3.3 Systems Engineering Life Cycle 35 1.3.4 Simulation of the System Development Process 38 1.3.5 Simulation-Based Systems Engineering 46 1.4 Summary 47 Problems 50 References 53 Bibliography 53 2 Simulation Concepts and Building Blocks 55 2.1 Statistical Aspects of Simulation 56 2.1.1 Convergence Theorems 57 2.1.2 Uniform Random-Number Generator 58 2.1.3 Discrete Probability Distributions 59 2.1.4 Goodness-of-Fit Test 60 2.1.5 Generation of Random Variables 62 2.2 OpEM Graphical Modeling Language 64 2.2.1 Petri Nets 65 2.2.2 OpEM Graphs 68 2.3 OpEM Parallel Process Simulations 72 2.3.1 Sequential Process Event 76 2.3.2 Split Event 78 2.3.3 Complex Assemble Event 80 2.3.4 Simple Assemble Event 83 2.3.5 Comparison of Petri Nets and OpEM Graphs 84 2.4 OpEMCSS Simulation of Context-Sensitive Systems 86 2.4.1 Types of CSS Process Interactions and Timeline Analysis 86 2.4.2 How ExtendSim Has Been Modified to Implement the OpEM Language 88 2.4.3 How OpEMCSS Blocks Work Together to Model an Example CSS 90 2.4.4 Summary 98 2.5 An OpEM Example of Preemptive Scheduling 99 2.6 Summary 112 Problems 114 References 118 Bibliography 119 3 Systems Design and Model Development 120 3.1 Inventory System 122 3.1.1 Inventory System Model Development 122 3.1.2 Inventory System Model Description 125 3.1.3 Inventory System Model Operation 132 3.1.4 Summary 132 3.2 Part Production System 134 3.2.1 Part Production System Model Development 134 3.2.2 Part Production System Model Description 137 3.2.3 Part Production System Model Operation 141 3.3 Seaport System 142 3.3.1 Seaport System Model Development 142 3.3.2 Seaport System Model Description 145 3.3.3 Seaport System Model Operation 151 3.4 Advanced Features of OpEMCSS 153 3.4.1 Expanded Split and Assemble Operation 154 3.4.2 Preemption of a Resource 167 3.4.3 “Wake Up” a Passivated Process 172 3.5 Summary 172 Problems 174 References 176 4 Markov Model Development 177 4.1 Discrete-Time Markov Chains 178 4.1.1 Stochastic Processes 178 4.1.2 Transition Probabilities 179 4.1.3 Properties of a Finite-State Markov Chain 180 4.1.4 Development of [P]n 181 4.1.5 Steady-State Solution 182 4.1.6 First-Passage Times 187 4.2 Continuous-Time Markov Processes 189 4.2.1 Poisson Distribution 189 4.2.2 Kolmogorov Differential Equations 191 4.2.3 Transition Intensities for Poisson Process 194 4.2.4 Transition Matrix for Several Examples 196 4.2.5 Markov Process Model of a Queuing System 199 4.2.6 Summary of Assumptions 203 4.3 Semi-Markov Flow Graphs 205 4.3.1 Definitions 206 4.3.2 Laplace Transforms 207 4.3.3 Flow-Graph Reduction 210 4.3.4 Thief of Baghdad Process 213 4.3.5 General Reaction Time Distributions 215 4.3.6 Summary of Flow-Graph Techniques 217 4.4 System Design and Evaluation Using Markov Models 217 4.4.1 Data Communications System Design Problem 217 4.4.2 Markov Model of Sequential Link Operation 219 4.4.3 Markov Model of Parallel Link Operation 222 4.4.4 Sensitivity of Link Effectiveness 227 4.4.5 Conclusions 232 Problems 234 References 237 Bibliography 237 5 Reliability Processes 238 5.1 Definitions 238 5.1.1 System 238 5.1.2 Multidimensional System Analysis 239 5.1.3 Equipment Dependency Diagrams 240 5.1.4 Reliability 241 5.1.5 Reliability Process 243 5.2 Reliability of Nonmaintained Module Groups 244 5.2.1 Method 244 5.2.2 Series Module Group 245 5.2.3 Parallel Module Group 246 5.2.4 Series–Parallel Module Group 246 5.2.5 Four-Module Group 247 5.2.6 Logic Techniques 248 5.3 Availability of Maintained Module Groups 249 5.3.1 Method 249 5.3.2 Series Module Group 249 5.3.3 Parallel Module Group 252 5.3.4 Analysis of Maintained Module Groups 253 5.4 Dependence of System Performance on Reliability 253 5.4.1 System of Three Radars and Two Detection Consoles 253 5.4.2 State-Space Equation 254 5.4.3 Validation of Model Results 256 5.4.4 Sensitivity Curve 257 5.5 Summary 258 Problems 258 Bibliography 260 6 Queuing Theory in Simulation-Based Systems Engineering 261 6.1 Single-Queue, Single-Server Process 262 6.1.1 Supermarket Checkout Stand 262 6.1.2 Parallel Process 263 6.1.3 Operational Sequence 265 6.1.4 Finite Queue Model 266 6.1.5 Infinite Queue Model 271 6.1.6 Gamma Service Time 274 6.2 Single-Queue, Two-Server Process 275 6.2.1 Bank 275 6.2.2 Parallel Process 275 6.2.3 Operational Sequence 277 6.2.4 Finite Queue Model 278 6.2.5 Infinite Queue Model 280 6.3 Comparison of Simulation, Markov Process, and Queuing Theory Models 281 Problems 283 Bibliography 285 7 Rule-Based Learning and Adaptation 286 7.1 Classifier Systems 287 7.2 Induction of Decision-Making Rules 289 7.2.1 Overview of the Rule Induction Problem 289 7.2.2 Situational Universe for a Classifier System 291 7.2.3 Lessons Learned from Previous Research 293 7.2.4 Theory of Inductive Learning of Decision-Making Rules 295 7.2.5 Summary of Induction Methods and Theory 297 7.3 Supervisory Rule Learning 297 7.3.1 Classifier Event Action Block 297 7.3.2 Induction Process Model 302 7.4 Generation of Planning Rules 308 7.4.1 Prisoner’s Dilemma 308 7.4.2 Finite-State Machine Model 313 7.4.3 Grid World Model 318 7.5 Summary 320 7.6 Conclusions 322 References 323 Bibliography 324 8 Agent Motion and Spatial Interactions 325 8.1 Discrete-Event Model of Continuous Motion 326 8.1.1 Range Closing/Range Not Closing Interaction 326 8.1.2 Angle Closing/Angle Not Closing Interaction 331 8.1.3 Intercept Interaction 334 8.2 Agent Motion and Spatial Interaction Blocks 335 8.2.1 Initialize Agent Event Action 335 8.2.2 Change Agent Event Action 336 8.2.3 Agent Interaction Event Action 338 8.2.4 Animation Event Action 342 8.3 World Model 343 8.4 Sonar Array System 354 8.5 Summary 366 Bibliography 368 9 Multiagent System of Systems 369 9.1 Agents and Agent Interactions 370 9.1.1 Agents 370 9.1.2 Agent Interactions in System of Systems 373 9.1.3 Bringing Multiagent Systems of Systems into Being 375 9.2 Elevator System 376 9.2.1 Person Arrival Process 376 9.2.2 Person Process 378 9.2.3 Elevator Motion Process 379 9.2.4 Evaluation of Elevator System Performance 382 9.3 Distributed, Vehicle Traffic Light Control System 383 9.3.1 Traffic Control Agent 384 9.3.2 Fuzzy Control 387 9.3.3 Simulation of a Vehicle Traffic Control Network 388 9.3.4 Results of Simulation Runs 392 9.4 Communication Blocks for Multiagent Systems 394 9.4.1 Memory Event Action Block 394 9.4.2 Analysis Event Action Block 397 9.4.3 Send Message Event Action Block 400 9.4.4 Plan Execution Event Action Block 401 9.4.5 Message Passing in a Multiagent System 402 9.5 Summary 406 References 408 Bibliography 409 Appendix A OpEMCSS User’s Manual 410 A.1 Minimum Requirements for Successful CSS Modeling Languages 411 A.2 Modeling Languages Survey 412 A.2.1 Petri Nets 412 A.2.2 IDEF0 Diagrams 412 A.2.3 ExtendSim Queuing Models 413 A.2.4 Modeling Languages Survey Summary 413 A.3 Operational Evaluation Modeling (OpEM) Historical Overview 413 A.4 OpEMCSS Familiarization Exercises 416 A.4.1 How to Set Up ExtendSim LT-RunTime 416 A.4.2 ExtendSim Environment Overview 418 A.4.3 Block Familiarization Exercises 424 A.5 Overview of Context-Sensitive Event Action Blocks 433 A.5.1 Message Event Action Block 433 A.5.2 Context-Sensitive Event Action Block 434 A.5.3 Event Action Block 434 A.6 Summary 434 References 435 Appendix B Overview of OpEMCSS Library Blocks 436 B.1 Definition of OpEMCSS Block Categories 436 B.2 Description of OpEMCSS Blocks by Category 437 B.2.1 Category 1 437 B.2.2 Category 2 439 B.2.3 Category 3 441 B.2.4 Category 4 444 B.2.5 Category 5 454 B.2.6 Category 6 464 B.2.7 Category 7 469 B.2.8 Category 8 473 B.2.9 Category 9 475 B.3 Summary of OpEMCSS Block Categories 476 Appendix C Programming OpEMCSS Special Blocks 477 C.1 Special Event Action Block Dialogs 478 C.2 Execute Event Action Procedure 478 C.3 Summary 484 Index 487