Stochastic Modeling and Analysis of Manufacturing Systems

David D. Yao

ISBN 10: 1461276284 / ISBN 13: 9781461276289

Published by Springer, Springer, 2013

About this Item

Druck auf Anfrage Neuware - Printed after ordering - Manufacturing systems have become increasingly complex over recent years. This volume presents a collection of chapters which reflect the recent developments of probabilistic models and methodologies that have either been motivated by manufacturing systems research or been demonstrated to have significant potential in such research. The editor has invited a number of leading experts to present detailed expositions of specific topics. These include: Jackson networks, fluid models, diffusion and strong approximations, the GSMP framework, stochastic convexity and majorization, perturbation analysis, scheduling via Brownian models, and re-entrant lines and dynamic scheduling. Each chapter has been written with graduate students in mind, and several have been used in graduate courses that teach the modeling and analysis of manufacturing systems.

Seller Inventory # 9781461276289

Bibliographic Details

• Title: Stochastic Modeling and Analysis of Manufacturing Systems
• Publisher: Springer, Springer
• Publication Date: 2013
• Language: English
• ISBN 10: 1461276284
• ISBN 13: 9781461276289
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 21D millimeters 235 millimeters width by 155 millimeters height by 21 millimeters depth
• Weight: 575 grams

About this title

Synopsis

Manufacturing systems have become increasingly complex over recent years. This volume presents a collection of chapters which reflect the recent developments of probabilistic models and methodologies that have either been motivated by manufacturing systems research or been demonstrated to have significant potential in such research.
The editor has invited a number of leading experts to present detailed expositions of specific topics. These include: Jackson networks, fluid models, diffusion and strong approximations, the GSMP framework, stochastic convexity and majorization, perturbation analysis, scheduling via Brownian models, and re-entrant lines and dynamic scheduling. Each chapter has been written with graduate students in mind, and several have been used in graduate courses that teach the modeling and analysis of manufacturing systems.

Review

"This is a very well-written book, providing a good balance between modeling and mathematical rigor....I enjoyed reading this book and will undoubtedly use it myself; I would also highly recommend it to my graduate students." - Technometrics