Discrete-event system simulation / Jerry Banks ... [et al.].

By: Banks, Jerry .

Contributor(s): Carson, John S | Nelson, Barry L .

Material type: materialTypeLabel

BookSeries: Prentice-Hall international series in industrial and systems engineering.Publisher: Upper Saddle River, N.J. : Prentice Hall, 2000Edition: 3rd ed.Description: xiv, 594 p. : ill. ; 24 cm.ISBN: 0130887021.Subject(s): Simulation methods

DDC classification: 003.83

Contents:

Part One: Introduction to Discrete-Event System Simulation -- Introduction to Simulation -- Simulation examples -- General Principles -- Simulation Software -- Part Two: Mathematical and Statistical Models -- Statistical Models in Simulation -- Queueing Models -- Part Three: Random Numbers -- Random-Number Generation -- Random-Variate Generation -- Part Four: Analysis of Simulation Data -- Input Modeling -- Verification and Validation of Simulation Models -- Output Analysis for a Single Model -- Comparison and Evaluation of Alternative System Designs -- Simulation of Manufacturing and Material Handling Systems -- Simulation of Computer Systems.

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Enhanced descriptions from Syndetics:

This book provides a basic treatment of discrete-event simulation, including the proper collection and analysis of data, the use of analytic techniques, verification and validation of models, and designing simulation experiments. Contains up-to-date treatment of simulation of manufacturing and material handling systems. Includes numerous solved examples. Offers an integrated website. Explains how to interpret simulation software output. For those interested in learning more about discrete-event simulation.

Includes bibliographical references and index.

Table of contents provided by Syndetics

I Introduction To Discrete-Event System Simulation
1 Introduction to Simulation
When Simulation Is the Appropriate Tool
When Simulation Is Not Appropriate
Advantages and Disadvantages of Simulation
Areas of Application
Systems and System Environment
Components of a System
Discrete and Continuous Systems
Model of a System
Types of Models
Discrete-Event System Simulation
Steps in a Simulation Study
2 Simulation Examples
Simulation of Queueing Systems
Simulation of Inventory Systems
Other Examples of Simulation
3 General Principles
Concepts in Discrete-Event Simulation
List Processing
4 Simulation Software
History of Simulation Software
Selection of Simulation Software
An Example Simulation
Simulation in C++
Simulation in GPSS
Simulation in CSIM
Simulation Packages
Experimentation and Statistical Analysis Tools
Trends in Simulation Software
II Mathematical And Statistical Models
5 Statistical Models in Simulation
Review of Terminology and Concepts
Useful Statistical Models
Discrete Distributions
Continuous Distributions
Poisson Process
Empirical Distributions
6 Queueing Models
Characteristics of Queueing Systems
Queueing Notation
Long-Run Measures of Performance of Queueing Systems
Steady-State Behavior of Infinite-Population Markovian Models
Steady-State Behavior of Finite-Population Models
Networks of Queues
III Random Numbers
7 Random-Number Generation
Properties of Random Numbers
Generation of Pseudo-Random Numbers
Techniques for Generating Random Numbers
Tests for Random Numbers
8 Random-Variate Generation
Inverse Transform Technique
Direct Transformation for the Normal and Lognormal Distributions
Convolution Method
Acceptance-Rejection Technique
IV Analysis Of Simulation Data
9 Input Modeling
Data Collection
Identifying the Distribution with Data
Parameter Estimation
Goodness-of-Fit Tests
Selecting Input Models without Data
Multivariate and Time-Series Input Models
10 Verification and Validation of Simulation Models
Model Building, Verification, and Validation
Verification of Simulation Models
Calibration and Validation of Models
11 Output Analysis for a Single Model
Types of Simulations with Respect to Output Analysis
Stochastic Nature of Output Data
Measures of Performance and Their Estimation
Output Analysis for Terminating Simulations
Output Analysis for Steady-State Simulations
12 Comparison and Evaluation of Alternative System Designs
Comparison of Two System Designs
Comparison of Several System Designs
Metamodeling
Optimization via Simulation
13 Simulation of Manufacturing and Material Handling Systems
Manufacturing and Material Handling Simulations
Goals and Performance Measures
Issues in Manufacturing and Material Handling Simulations
Case Studies of the Simulation of Manufacturing and Material Handling Systems
14 Simulation of Computer Systems
Introduction
Simulation Tools
Model Input
High-Level Computer-System Simulation
CPU Simulation
Memory Simulation
Appendix Tables
Random Digits
Random Normal Numbers
Cumulative Normal Distribution
Cumulative Poisson Distribution
Percentage Points of the Students
Distribution with
Degrees of Freedom
Percentage Points of the Chi-Square Distribution with v
Degrees of Freedom
Percentage Points of the F
Distribution with âÇ a = 0.05
Kolmogorov-Smirnov Critical Values
Maximum-Likelihood Estimates of the Gamma Distribution
Operating-Characteristic Curves for the Two-Sided t-Test for Different Values of Sample Size
Operating-Characteristic Curves for the One-Sided t-Test for Different Values of Sample Size
Index