Authors:
- Provides timeless methods for measuring statistics and probabilities in a vast range of queuing systems
- Presents information that is critical for professionals, researchers, and students in management science
- Features a tested format without difficult mathematical formulas or equations
- Each of the 23 chapters includes useful examples, problems and solutions
- Includes supplementary material: sn.pub/extras
Buy it now
Buying options
Tax calculation will be finalised at checkout
Other ways to access
This is a preview of subscription content, log in via an institution to check for access.
Table of contents (23 chapters)
-
Front Matter
About this book
Waiting in lines is a staple of everyday human life. Without really noticing, we are doing it when we go to buy a ticket at a movie theater, stop at a bank to make an account withdrawal, or proceed to checkout a purchase from one of our favorite department stores. Oftentimes, waiting lines are due to overcrowded, overfilling, or congestion; any time there is more customer demand for a service than can be provided, a waiting line forms. Queuing systems is a term used to describe the methods and techniques most ideal for measuring the probability and statistics of a wide variety of waiting line models. This book provides an introduction to basic queuing systems, such as M/M/1 and its variants, as well as newer concepts like systems with priorities, networks of queues, and general service policies. Numerical examples are presented to guide readers into thinking about practical real-world applications, and students and researchers will be able to apply the methods learned to designing queuing systems that extend beyond the classroom. Very little has been published in the area of queuing systems, and this volume will appeal to graduate-level students, researchers, and practitioners in the areas of management science, applied mathematics, engineering, computer science, and statistics.
Reviews
From the reviews:
“Fundamentals of Queuing Systems: Statistical Methods for Analyzing Queuing Models is a queuing theory book with practitioners as its target audience. … the consideration of a number of special cases permits the author to provide tailored solutions to specific problems, an ideal situation for the reader who is looking for some formulae for those problems. … Many real-world numerical examples are scattered throughout the book to provide the reader with opportunities to see how the formulae work.” (David Hodge, Interfaces, Vol. 43 (6), November-December, 2013)Authors and Affiliations
-
, Stuart School of Business, Illinois Institute of Technology, Burr Ridge, USA
Nick T. Thomopoulos
About the author
Nick T. Thomopoulos is a professor emeritus at the Illinois Institute of Technology. He is the author of four books, including Quantitative Methods Along the Supply Chain (Atlantic Publishers, 2011). He has over 100 published papers and presentations to his credit, and for many years, he has consulted in a wide variety of industries in the United States, Europe, and Asia. He has been the recipient of numerous honors, such as the Rist Prize in 1972 from the Military Operations Research Society for new developments in queuing theory, the Distinguished Professor Award in Bangkok, Thailand in 2005 from the IIT Asian Alumni Association, and the Professional Achievement Award in 2009 from the IIT Alumni Association.
Bibliographic Information
Book Title: Fundamentals of Queuing Systems
Book Subtitle: Statistical Methods for Analyzing Queuing Models
Authors: Nick T. Thomopoulos
DOI: https://doi.org/10.1007/978-1-4614-3713-0
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Science+Business Media New York 2012
Hardcover ISBN: 978-1-4614-3712-3
Softcover ISBN: 978-1-4899-9203-1
eBook ISBN: 978-1-4614-3713-0
Edition Number: 1
Number of Pages: XVIII, 182
Topics: Statistics for Business, Management, Economics, Finance, Insurance, Operations Research/Decision Theory, Operations Research, Management Science