Stochastic Models in Operations Research, Vol. I: Stochastic Processes and Operating Characteristics (Dover Books on Computer Science)

Heyman, Daniel P.; Sobel, Matthew J.

ISBN 10: 0486432599 / ISBN 13: 9780486432595

Published by Dover Publications, 2003

About this Item

The item is very worn but is perfectly usable. Signs of wear can include aesthetic issues such as scratches, dents, worn and creased covers, folded page corners and minor liquid stains. All pages and the cover are intact, but the dust cover may be missing. Pages may include moderate to heavy amount of notes and highlighting, but the text is not obscured or unreadable. Page edges may have foxing age related spots and browning . May NOT include discs, access code or other supplemental materials.

Seller Inventory # BVV.0486432599.A

Bibliographic Details

• Title: Stochastic Models in Operations Research, Vol. I: Stochastic Processes and Operating Characteristics (Dover Books on Computer Science)
• Publisher: Dover Publications
• Publication Date: 2003
• Language: English
• ISBN 10: 0486432599
• ISBN 13: 9780486432595
• Binding: Soft cover
• Condition: acceptable

About this title

Synopsis

The first of a two-volume set begins with discussions of stochastic processes, including posterity analysis, birth-and-death processes, renewal theory, renewal-reward and regenerative processes, Markov chains, continuous-time Markov chains, Markov processes, and stationery processes and ergodic theory. Its coverage of operating characteristics of stochastic systems examines system properties, networks of queues, and bounds and approximations.
This two-volume set of texts explores the central facts and ideas of stochastic processes, illustrating their use in models based on applied and theoretical investigations. They demonstrate the interdependence of three areas of study that usually receive separate treatments: stochastic processes, operating characteristics of stochastic systems, and stochastic optimization.
Comprehensive in its scope, this work emphasizes the practical importance, intellectual stimulation, and mathematical elegance of stochastic models. It is intended primarily as a graduate-level text for studies in operations research, management science, computer science, and all branches of engineering, applied mathematics, statistics, and economics.