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Sinopsis
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.
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Rutgers University, New Brunswick, NJ
De la contraportada
[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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