Simulation Modeling and Analysis
5th Edition
Published on 16. February 2014
Book
Hardback
800 pages
978-0-07-340132-4 (ISBN)
Description
Simulation Modeling and Analysis provides a comprehensive, state-of-the-art, and technically correct treatment of all important aspects of a simulation study. The book strives to make this material understandable by the use of intuition and numerous figures, examples, and problems. It is equally well suited for use in university courses, simulation practice, and self-study. The book is widely regarded as the "bible" of simulation and now has more than 172,000 copies in print and has been cited more than 18,500 times. This textbook can serve as the primary text for a variety of courses. It is used in leading industrial and systems engineering departments at Georgia Tech, University of Michigan, University of California at Berkeley, Stanford University, Purdue University, Texas A&M University, Columbia University, University of Washington, and Naval Postgraduate School.
More details
Edition
5th edition
Language
English
Place of publication
London
United States
Publishing group
McGraw-Hill Education - Europe
Target group
College/higher education
US School Grade: College Freshman
Illustrations
312 Illustrations
Dimensions
Height: 244 mm
Width: 168 mm
Thickness: 36 mm
Weight
1168 gr
ISBN-13
978-0-07-340132-4 (9780073401324)
Schweitzer Classification
Other editions
New editions
Averill Law
Simulation Modeling and Analysis, Sixth Edition
Book
03/2024
6th Edition
McGraw-Hill Education
€146.80
Available immediately
Person
Averill M. Law is President of Averill M. Law & Associates, Inc. (Tucson, AZ), a company specializing in simulation training, consulting, and software. He was previously Professor of Decision Sciences at the University of Arizona and Associate Professor of Industrial Engineering at the University of Wisconsin-Madison. He has a Ph.D. and an M.S. in industrial engineering and operations research from the University of California at Berkeley, an M.A. in mathematics from California State University-Long Beach, and a B.S. in mathematics from Pennsylvania State University. Dr. Law has been a simulation consultant to organizations such as Accenture, Boeing, Booz Allen & Hamilton, ConocoPhillips, Defense Modeling and Simulation Office, Federal Express, Ford, Hewlett-Packard, Kimberly-Clark, M&M/Mars, Monsanto, Sandia National Labs, Swedish Defense Material Administration, U.S. Marine Corps, and Xerox. He has presented more than 550 simulation and statistics short courses in 20 countries, including onsite seminars for ALCOA, AT&T, Boeing, Caterpillar, Coca-Cola, CSX, GE, GM, IBM, Intel, Lockheed Martin, Los Alamos National Lab, Missile Defense Agency, Motorola, NASA, National Security Agency, Northrop Grumman, 3M, Time Warner, UPS, U.S. Air Force, U.S. Army, U.S. Navy, and Whirlpool. He is the developer of the ExpertFit distribution-fitting software, which automates the selection of simulation input probability distributions. ExpertFit is used by more than 3000 organizations worldwide. He also developed the videotapes "Simulation of Manufacturing Systems" and "How to Conduct a Successful Simulation Study." Dr. Law is the author (or coauthor) of three books and numerous papers on simulation, operations research, statistics, manufacturing, and communications networks. His article "Statistical Analysis of Simulation Output Data" was the first invited feature paper on simulation to appear in a major research journal. His series of papers on the simulation of manufacturing systems won the 1988 Institute of Industrial Engineers' best publication award. He was awarded the 2009 INFORMS Simulation Society's Lifetime Professional Achievement Award for his simulation seminars and book. During his academic career, the Office of Naval Research supported his simulation research for 8 consecutive years. He wrote a regular column on simulation for "Industrial Engineering" during 1990 and 1991.
Content
1) Basic Simulation Modeling
2) Modeling Complex Systems
3) Simulation Software
4) Review of Basic Probability and Statistics
5) Building Valid, Credible, and Appropriately Detailed Simulation Models
6) Selecting Input Probability Distributions
7) Random-Number Generators
8) Generating Random Variates
9) Output Data Analysis for a Single System
10) Comparing Alternative System Configurations
11) Variance-Reduction Techniques
12) Experimental Design, Sensitivity Analysis, and Optimization
13) Simulation of Manufacturing Systems
2) Modeling Complex Systems
3) Simulation Software
4) Review of Basic Probability and Statistics
5) Building Valid, Credible, and Appropriately Detailed Simulation Models
6) Selecting Input Probability Distributions
7) Random-Number Generators
8) Generating Random Variates
9) Output Data Analysis for a Single System
10) Comparing Alternative System Configurations
11) Variance-Reduction Techniques
12) Experimental Design, Sensitivity Analysis, and Optimization
13) Simulation of Manufacturing Systems