Discrete-event System Simulation 5th Edition (pearson New International Edition)

By (author) Banks, Jerry; By (author) Carson, John S.; By (author) Nelson, Barry L.; By (author) Nicol David
Description
For junior- and senior-level simulation courses in engineering, business, or computer science. 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 Appendix Index
Feature
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.
New feature
New treatment of input modeling highlights difficulties and solutions for real applications. Updated examples of simulation experiment design and analysis are provided. More Excel examples and supplements enhance the material. A more realistic presentation of input modeling in Chapter 9. Emphasis on appropriate analysis within the confines of commercial products, and a supplementary Excel tool that adds to the capabilities of those products. — Addresses that some texts present advanced simulation analysis methods that cannot be used in practice if they are not included in the software the practitioner actually uses, or are not readily available as a supplementary tool.