Markovian Demand Inventory Models
(Sprache: Englisch)
This text provides a superbly researched insight into Markovian demand inventory models. The result of ten years of research, this work covers all aspects of demand inventory where they are modeled by Markov processes. Inventory management is concerned...
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Klappentext zu „Markovian Demand Inventory Models “
This text provides a superbly researched insight into Markovian demand inventory models. The result of ten years of research, this work covers all aspects of demand inventory where they are modeled by Markov processes. Inventory management is concerned with matching supply with demand and is a central problem in Operations Management. The central 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.
Inhaltsverzeichnis zu „Markovian Demand Inventory Models “
I INTRODUCTION.- II DISCOUNTED COST MODELS.- Discounted Cost Models with Backorders.- Discount Cost Models with Polynomially Growing Surplus Cost.- Discounted Cost Models with Lost Sales.- III AVERAGE COST MODELS.- Average Cost Models with Backorders.- Average Cost Models with Polynomially Growing Surplus Cost.- Average Cost Models with Lost Sales.- IV MISCELLANEOUS.- Models with Demand Influenced by Promotion.- Vanishing Discount Approach Versus Stationary Distribution Approach.- V CONCLUSIONS AND OPEN RESEARCH PROBLEMS.- Conclusions and Open Research Problems.
Bibliographische Angaben
- Autoren: Dirk Beyer , Feng Cheng , Suresh P. Sethi
- 2009, 255 Seiten, Maße: 16,4 x 24,3 cm, Gebunden, Englisch
- Verlag: Springer
- ISBN-10: 0387716033
- ISBN-13: 9780387716039
Sprache:
Englisch
Rezension zu „Markovian Demand Inventory Models “
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)
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