Simulation Modeling and Analysis with ARENA

Simulation Modeling and Analysis with Arena is a highly readable textbook which treats the essentials of the Monte Carlo discrete-event simulation methodology, and does so in the context of a popular Arena simulation environment.” It treats simulation modeling as an in-vitro laboratory that facilitates the understanding of complex systems and experimentation with what-if scenarios in order to estimate their performance metrics. The book contains chapters on the simulation modeling methodology and the underpinnings of discrete-event systems, as well as the relevant underlying probability, statistics, stochastic processes, input analysis, model validation and output analysis. All simulation-related concepts are illustrated in numerous Arena examples, encompassing production lines, manufacturing and inventory systems, transportation systems, and computer information systems in networked settings.

· Introduces the concept of discrete event Monte Carlo simulation, the most commonly used methodology for modeling and analysis of complex systems
· Covers essential workings of the popular animated simulation language, ARENA, including set-up, design parameters, input data, and output analysis, along with a wide variety of sample model applications from production lines to transportation systems
· Reviews elements of statistics, probability, and stochastic processes relevant to simulation modeling
* Ample end-of-chapter problems and full Solutions Manual
* Includes CD with sample ARENA modeling programs

[Academic PRESS LOGO]

Technology: Engineering. General

Simulation Modeling and Analysis with Arena
Tayfur Altiok
Professor, Department of Industrial & Systems Engineering, Rutgers University
Piscataway, New Jersey
Benjamin Melamed
Professor, Department of Management Science and Information Systems, Rutgers University, Piscataway, New Jersey

KEY FEATURES
· Introduces the concept of discrete event Monte Carlo simulation, the most commonly used methodology for modeling and analysis of complex systems
· Covers essential workings of the popular animated simulation language Arena, including set-up, design parameters, input data, and output analysis
· Reviews elements of statistics, probability, and stochastic processes relevant to simulation modeling
· Chapters are devoted to a variety of Arena models capturing a range of real-world applications, including production lines, supply chains, transportation, and computer information systems.

Simulation Modeling and Analysis with Arena is a highly readable textbook which treats the essentials of the Monte Carlo discrete-event simulation methodology, and does so in the context of a popular Arena simulation environment.? It treats simulation modeling as an in-vitro laboratory that facilitates the understanding of complex systems and experimentation with what-if scenarios in order to estimate their performance metrics. The book contains chapters on the simulation modeling methodology and the underpinnings of discrete-event systems, as well as the relevant underlying probability, statistics, stochastic processes, input analysis, model validation and output analysis. All simulation-related concepts are illustrated in numerous Arena examples, encompassing production lines, manufacturing and inventory systems, transportation systems, and computer information systems in networked settings.

Contents: Chapter 1 Introduction to Simulation Modeling; Chapter 2 Discrete Event Simulation; Chapter 3 Elements of Probability and Statistics; Chapter 4 Random Number and Variate Generation; Chapter 5 Arena Basics; Chapter 6 Model Testing and Debugging Facilities; Chapter 7 Input Analysis; Chapter 8 Model Goodness: Verification and Validation; Chapter 9 Output Analysis; Chapter 10 Correlation Analysis; Chapter 11 Modeling Production Lines; Chapter 12 Modeling Supply Chain Systems; Chapter 13 Modeling Transportation Systems; Chapter 14 Modeling Computer Information Systems; Appendix A Frequently Used Arena Constructs; Appendix B VBA in Arena.

Related titles:
Boucher: Design of Industrial Information Systems, 0-12-370492-8
Ross: Simulation, 3rd edition, 0-12-598063-9
Nelson et al: Introductory Statistics for Engineering Experimentation, 0-12-515423-2|[Academic PRESS LOGO]

Technology: Engineering. General

Simulation Modeling and Analysis with Arena
Tayfur Altiok
Professor, Department of Industrial & Systems Engineering, Rutgers University
Piscataway, New Jersey
Benjamin Melamed
Professor, Department of Management Science and Information Systems, Rutgers University, Piscataway, New Jersey

KEY FEATURES
· Introduces the concept of discrete event Monte Carlo simulation, the most commonly used methodology for modeling and analysis of complex systems
· Covers essential workings of the popular animated simulation language Arena, including set-up, design parameters, input data, and output analysis
· Reviews elements of statistics, probability, and stochastic processes relevant to simulation modeling
· Chapters are devoted to a variety of Arena models capturing a range of real-world applications, including production lines, supply chains, transportation, and computer information systems.

Simulation Modeling and Analysis with Arena is a highly readable textbook which treats the essentials of the Monte Carlo discrete-event simulation methodology, and does so in the context of a popular Arena simulation environment. It treats simulation modeling as an in-vitro laboratory that facilitates the understanding of complex systems and experimentation with what-if scenarios in order to estimate their performance metrics. The book contains chapters on the simulation modeling methodology and the underpinnings of discrete-event systems, as well as the relevant underlying probability, statistics, stochastic processes, input analysis, model validation and output analysis. All simulation-related concepts are illustrated in numerous Arena examples, encompassing production lines, manufacturing and inventory systems, transportation systems, and computer information systems in networked settings.

Contents: Chapter 1 Introduction to Simulation Modeling; Chapter 2 Discrete Event Simulation; Chapter 3 Elements of Probability and Statistics; Chapter 4 Random Number and Variate Generation; Chapter 5 Arena Basics; Chapter 6 Model Testing and Debugging Facilities; Chapter 7 Input Analysis; Chapter 8 Model Goodness: Verification and Validation; Chapter 9 Output Analysis; Chapter 10 Correlation Analysis; Chapter 11 Modeling Production Lines; Chapter 12 Modeling Supply Chain Systems; Chapter 13 Modeling Transportation Systems; Chapter 14 Modeling Computer Information Systems; Appendix A Frequently Used Arena Constructs; Appendix B VBA in Arena.

Related titles:
Boucher: Design of Industrial Information Systems, 0-12-370492-8
Ross: Simulation, 3rd edition, 0-12-598063-9
Nelson et al: Introductory Statistics for Engineering Experimentation, 0-12-515423-2

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