Simulation-Based Engineering of 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
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.
1. Introduction to Simulation-Based Systems Engineering.
1.1 Definition of Complex Systems.
1.2 Using Simulation to Understand Complex Systems.
1.3 Bringing Complex Systems into Being.
1.5 Homework Problems.
2. Simulation Concepts and Building Blocks.
2.1 Statistical Aspects of Simulation.
2.2 OpEM Graphical Modeling Language.
2.3 How OpEM Parallel Process Simulations Work.
2.4 OpEMCSS Simulation of Context-Sensitive Systems.
2.5 An OpEM Example of Preemptive Scheduling.
3. Systems Design and Model Development.
3.1 Inventory System.
3.2 Part Production System.
3.3 Seaport System.
3.4 Advanced Features of OpEMCSS.
4. Markov Model Development.
4.1 Discrete-Time Markov Chains.
4.2 Continuous-Time Markov Processes.
4.3 Semi-Markov Flow Graphs.
4.4 System Design and Evaluation Using Markov Models.
5. Reliability Processes.
5.2 Reliability of Non-Maintained Module Groups.
5.3 Availability of Maintained Module Groups.
5.4 Dependence of System Performance on Reliability.
6. Queuing Theory in Simulation-Based Systems Engineering.
6.1 Single-Queue, Single Server Process.
6.2 Single-Queue, Two-Server Process.
6.3 Comparison of Simulation, Markov Process, and Queuing Theory Models.
7. Rule-Based Learning and Adaptation.
7.1 Classifier Systems.
7.2 Induction of Decision Making Rules.
7.3 Supervisory Rule Learning.
8. Agent Motion and Spatial Interactions.
8.1 Discrete Event Model of Continuous motion.
8.2 Agent Motion and Spatial Interaction Blocks.
8.3 World Model.
8.4 Sonar Array System.
9. Multi-Agent System of Systems (SOS).
9.1 Agents and Agent Interactions.
9.2 Elevator System.
9.3 Distributed, Vehicle Traffic Light Control System.
9.4 Communication Blocks for Multi-Agent Systems.
Appendix A - OpEMCSS User’s Manual.
A.1 Minimum Requirements for Successful CSS Modeling Languages.
A.2 Modeling Languages Survey.
A.2.1 Petri Nets.
A.2.2 IDEF0 Diagrams.
A.2.3 ExtendSim Queuing Models.
A.2.4 Modeling Languages Survey Summary.
A.3 Operational Evaluation Modeling (OpEM) Historical Overview.
A.4 OpEMCSS Familiarization Exercises.
A.4.1 How to Set Up ExtendSim LT-RunTime.
A.4.2 ExtendSim Environment Overview.
A.4.3 Block Familiarization Exercises.
A.5 Overview of Context-Sensitive Event Action Blocks.
A.5.1 Message Event Action block.
A.5.2 Context-Sensitive Event Action block.
A.5.3 Event Action block.
Appendix B Overview of OpEMCSS Library Blocks.
B.1 Definition of OPEMCSS Block Categories.
B.2 Description of OpEMCSS Blocks by Category.
B.2.1 Category 1.
B.2.2 Category 2.
B.2.3 Category 3.
B.2.4 Category 4.
B.2.5 Category 5.
B.2.6 Category 6.
B.2.7 Category 7.
B.2.8 Category 8.
B.2.9 Category 9.
B.3 Summary of OpEMCSS Block Categories.
Appendix C - Programming OpEMCSS Special Blocks.
C.1 Special Event Action Block Dialogs.
C.2 Execute Event Action Procedure.
John R. Clymer, PhD, is a Professor at California State University at Fullerton.
Simulation-Based Engineering of Complex Systems (US $162.00)
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