Discrete Event System Simulation 5th Edition

629.00

  • Author: Jerry Banks John S. Carson, II Barry L. Nelson David M. Nicol
  • Publisher: Pearson
  • ISBN-13: 9789332518759
  • Pages: 530
  • Binding: Paperback
  • Year of Pub / Reprint Year: 2015

Description

About The Book

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.

Table Of Contents

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

Salient Features

• 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.