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Discrete-Event System Simulation, 5/e


Discrete-Event System Simulation, 5/e
Author(s)  Jerry Banks, David M. Nicol, Barry L. Nelson, John S. Carson and II
ISBN  9789332518759
Imprint  Pearson Education
Copyright  2014
Pages  530
Binding  Paperback
List Price  Rs. 935.00
  
 
 

While most books on simulation focus on particular software tools, Discrete Event System Simulation examines the principles of modeling and analysis that translate to all such tools. This language-independent text explains the basic aspects of the technology, including the proper collection and analysis of data, the use of analytic techniques, verification and validation of models, and designing simulation experiments. It offers an up-to-date treatment of simulation of manufacturing and material handling systems, computer systems, and computer networks.

  • About the Authors
  • Contents
  • Features
  • Downloadable Resources

Jerry Banks retired in 1999 as a professor in the School of Industrial and Systems Engineering, Georgia Institute of Technology, after which he worked as senior simulation technology advisor for Brooks Automation; he is currently a professor at Techno´ogico de Monterrey, M´exico. He is the author, coauthor, editor, or coeditor of twelve books, one set of proceedings, several chapters in texts, and numerous technical papers.



John S. Carson II is an independent simulation consultant. Formerly, he held management and consulting positions in the simulation services and software industry, including positions atAutoSimulations and the AutoMod Group at Brooks Automation. He was the co-founder and president of the simulation services firm Carson/Banks &Associates. He has over 30 years experience in simulation in a wide range of application areas, including manufacturing, distribution, warehousing and material handling, order fulfillment systems, postal systems, transportation and rapid transit systems, port operations (container terminals and bulk handling), and health-care systems. He has taught simulation and operations research at the Georgia Institute of Technology and the University of Florida.



Barry L. Nelson is the Charles Deering McCormick Professor and Chair of the Department of Industrial Engineering and Management Sciences at Northwestern University. His research centers on the design and analysis of computer simulation experiments on models of stochastic systems, concentrating on multivariate input modeling and output analysis, optimization via simulation and metamodeling.



David M. Nicol is professor of electrical and computer engineering at the University of Illinois at Urbana-Champaign. He is a long-time contributor in the field of parallel and distributed discrete-event simulations, having written one of the early Ph.D. dissertations on the topic. He has also worked in parallel algorithms, algorithms for mapping workload in parallel architectures, performance analysis, and reliability modeling and analysis.


 

 

I Introduction to Discrete-Event System Simulation


Chapter 1 Introduction to Simulation


Chapter 2 Simulation Examples


Chapter 3 General Principles


Chapter 4 Simulation Software


II Mathematical and Statistical Models


Chapter 5 Statistical Models in Simulation


Chapter 6 Queueing Models


III Random Numbers


Chapter 7 Random-Number Generation


Chapter 8 Random-Variate Generation


IV Analysis of Simulation Data


Chapter 9 Input Modeling


Chapter 10 Verification and Validation of Simulation Models


Chapter 11 Output Analysis for a Single Model


Chapter 12 Comparison and Evaluation of Alternative System Designs


V Applications


Chapter 13 Simulation of Manufacturing and Material-Handling Systems


Chapter 14 Simulation of Computer Networks



 

 

• Simulation of Communications Systems includes new material on simulation beta distribution, negative binomial distribution and non-stationary processes.


• Subset selection methods used for output analysis of several alternatives are discussed.


• Numerous solved examples enhance understanding of concepts.


• Abundant figures, tables and end-chapter exercises are provided.


• Application topics promote understanding of real-world uses.


• Interpretation of simulation software output explains how to use software tools correctly.


• Discussion of simple tools for complex input modeling problems develops more realistic valid models.


 

 
 
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