Stochastic Modeling and Analysis of Manufacturing Systems

✍ Scribed by John A. Buzacott, J. George Shanthikumar (auth.), David D. Yao (eds.)

Publisher: Springer-Verlag New York
Year: 1994
Tongue: English
Leaves: 368
Series: Springer Series in Operations Research
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ 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.

✦ Table of Contents

Front Matter....Pages i-xv
Jackson Network Models of Manufacturing Systems....Pages 1-45
Hierarchical Modeling of Stochastic Networks, Part I: Fluid Models....Pages 47-105
Hierarchical Modeling of Stochastic Networks, Part II: Strong Approximations....Pages 107-131
A GSMP Framework for the Analysis of Production Lines....Pages 133-188
Stochastic Convexity and Stochastic Majorization....Pages 189-231
Perturbation Analysis of Production Networks....Pages 233-280
Scheduling Networks of Queues: Heavy Traffic Analysis of a Bi-Criteria Problem....Pages 281-323
Scheduling Manufacturing Systems of Re-Entrant Lines....Pages 325-360

✦ Subjects

Operations Research/Decision Theory; Production/Logistics/Supply Chain Management; Economic Theory

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