Authors:
- Only book coverage of this important area of research
- Suresh Sethi is the most renowned researcher in the field
- Appropriate for researchers, practitioners, and Ph.D. students
- Includes supplementary material: sn.pub/extras
Part of the book series: International Series in Operations Research & Management Science (ISOR, volume 108)
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Table of contents (10 chapters)
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Front Matter
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Introduction
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Front Matter
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Part I INTRODUCTION
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Discounted Cost Models
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Front Matter
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Average Cost Models
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Front Matter
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Miscellaneous
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Front Matter
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Conclusions and Open Research Problems
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Front Matter
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Part V CONCLUSIONS AND OPEN RESEARCH PROBLEMS
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Back Matter
About this book
Inventory management is concerned with matching supply with demand and a central problem in Operations Management. The problem is to find the amount to be produced or purchased in order to maximize the total expected profit or minimize the total expected cost. Over the past two decades, several variations of the formula appeared, mostly in trade journals written by and for inventory managers. A critical assumption in the inventory literature is that the demands in different periods are independent and identically distributed. However, in real life, demands may depend on environmental considerations or the events in the world such as the weather, the state of economy, etc. Moreover, these events are represented by stochastic processes - exogenous or controlled.
In Markovian Demand Inventory Models, the authors are concerned with inventory models where these world events are modeled by Markov processes. Their research on Markovian demand inventory models was carried out over a period of ten years beginning in the early nineties.
Keywords
Reviews
From the reviews:
“In this book, the authors present a complete, rigorous mathematical treatment of the classical dynamic inventory models with stochastic demands. … This book is an elegant and comprehensive account of Markovian demand inventory models. It will be useful for students, researchers and practitioners in operations management and industrial engineering.” (P. R. Parthasarathy, Mathematical Reviews, Issue 2012 g)Authors and Affiliations
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M-Factor, Inc., San Mateo, U.S.A.
Dirk Beyer
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T.J. Watson Research Center, IBM Corporation, Yorktown Heights, U.S.A.
Feng Cheng
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School of Management, University of Texas, Dallas, Richardson, U.S.A.
Suresh P. Sethi
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Dept. Mathematics, University of Missouri, Columbia, Columbia, U.S.A.
Michael Taksar
Bibliographic Information
Book Title: Markovian Demand Inventory Models
Authors: Dirk Beyer, Feng Cheng, Suresh P. Sethi, Michael Taksar
Series Title: International Series in Operations Research & Management Science
DOI: https://doi.org/10.1007/978-0-387-71604-6
Publisher: Springer New York, NY
eBook Packages: Business and Economics, Business and Management (R0)
Copyright Information: Springer-Verlag US 2010
Hardcover ISBN: 978-0-387-71603-9Published: 16 October 2009
Softcover ISBN: 978-1-4614-2466-6Published: 25 February 2012
eBook ISBN: 978-0-387-71604-6Published: 03 October 2009
Series ISSN: 0884-8289
Series E-ISSN: 2214-7934
Edition Number: 1
Number of Pages: XX, 255
Number of Illustrations: 15 b/w illustrations
Topics: Business Mathematics, Operations Research/Decision Theory, Operations Research, Management Science, Operations Management, Probability Theory and Stochastic Processes, Engineering Economics, Organization, Logistics, Marketing