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Simulation Modeling and Arena

Simulation Modeling and Arena

Manuel D. Rossetti

ISBN: 978-0-470-47266-8

Apr 2012

600 pages


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Traditionally, there have been two primary types of simulation textbooks: those that emphasize the theoretical (and mostly statistical) aspects of simulation, and those that emphasize the simulation language or package.  Simulation Modeling and Arena blends these two aspects of simulation textbooks together while adding and emphasizing the art of model building.  The text contains chapters on modeling and chapters that emphasize the statistical aspects of simulation, but the coverage of statistical analysis is integrated with the modeling to emphasize the importance of both topics.  Simulation Modeling and Arena utilizes the Arena Simulation Environment--one of the leading simulation modeling packages in the world--as the primary modeling tool for teaching simulation.  While the book uses Arena as the primary modeling tool, the text is not intended to be a "user's guide to Arena;"  instead, Arena is used as the vehicle for explaining important simulation concepts.

Simulation Modeling and Arena is intended for a first course in discrete-event simulation modeling and analysis for upper-level undergraduate students as well as entering graduate students.  While the text is focused towards engineering students (primarily industrial engineering) it could also be utilized by advanced business majors, computer science majors, and other disciplines where simulation is practiced.  Practitioners interested in learning simulation and Arena could also use this book independently of a course.

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Chapter 1. Simulation Modeling.

1. Simulation Modeling.

1.1 Why Simulate?

1.2 Types of Computer Simulation.

1.3 How the Discrete-Event Clock Works.

1.4 Randomness in Simulation.

1.5 Simulation Languages.

1.6 Getting Started with Arena.

1.7 Getting Help within Arena.

1.8 Simulation Methodology.

1.9 Organization of the Book.

1.10 Exercises.

Chapter 2. Basic Process Modeling.

2. Elements of Process-Oriented Simulation.

2.1 Entities, Attributes, and Variables.

2.2 Creating and Disposing of Entities.

2.3 Defining Variables and Attributes.

2.4 Processing Entities.

2.5 Attributes, Variables, and some I/O.

2.6 Flow of Control in Arena.

2.7 Batching and Separating Entities.

2.8 SIMAN and Arena's Run Controller.

2.9 Summary.

2.10 Exercises.

Chapter 3. Modeling Randomness in Simulation.

3. Modeling Randomness in Simulation.

3.1 Random Variables and Probability Distributions.

3.2 Input Distribution Modeling.

3.3 Generating Random Numbers.

3.4 Summary.

3.5 Exercises.

3.6 Appendix: Using MINITAB and BestFit during Input Modeling.

3.7 Appendix: Basic Spreadsheet Simulation Concepts.

Chapter 4. Analyzing Simulation Output.

4. Analyzing Simulation Output.

4.1 Types of Statistical Variables.

4.2 Types of Simulation With Respect To Output Analysis.

4.3 Analysis of Finite Horizon Simulations.

4.4 Analysis of Infinite Horizon Simulations.

4.5 Comparing System Configurations.

4.6 Summary.

4.7 Exercises.

Chapter 5. Modeling Queueing and Inventory Systems.

5. Introduction.

5.1 Single Line Queueing Stations.

5.2 Networks of Queueing Stations.

5.3 Inventory Systems.

5.4 Summary.

5.5 Exercises.

Chapter 6. Entity Movement and Material Handling Constructs.

6. Introduction.

6.1 Constrained Transfer with Resources.

6.2 Constrained Transfer with Transporters.

6.3 Modeling Systems with Conveyors.

6.4 Modeling Guided Path Transporters.

6.5 Summary.

6.6 Exercises.

Chapter 7. Miscellaneous Topics in Arena Modeling.

7. Introduction.

7.1 Advanced Resource Modeling.

7.2 Tabulating Frequencies using the STATISTIC Module.

7.3 Entity and Resource Costing.

7.4 Miscellaneous Modeling Concepts.

7.5 Programming Concepts within Arena.

7.6 Summary.

7.7 Exercises.

Chapter 8. Application of Simulation Modeling.

8. Introduction.

8.1 Problem Description.

8.2 Detailed Solution.

8.3 Sensitivity Analysis.

8.4 Completing the Project.

8.5 Some Final Thoughts.

8.6 Exercises.



  • Integrated statistical analysis: comprehensive coverage of major statistical concepts allows one book to serve in the place of two
  • Hands on learning: enhances student retention of material and preparation for exams/projects
  • Treats subject from computer programming point of view: allows students to build on prior programming skills
  • Integrates conceptual modeling with model building:  teaches students to develop and communicate their models without Arena
  • Coverage of queuing and inventory models: provides background for building more complex models
  • Comprehensive examples and problems sets for enhanced student learning
  • Bundled Arena software and textbook files: students will have all the tools and files needed for the book on one resource