Foundations of Stochastic Inventory Theory

Foundations of Stochastic Inventory Theory

by Evan Porteus
     
 

ISBN-10: 0804743991

ISBN-13: 9780804743990

Pub. Date: 08/28/2002

Publisher: Stanford University Press


In 1958, Stanford University Press published Studies in the Mathematical Theory of Inventory and Production (edited by Kenneth J. Arrow, Samuel Karlin, and Herbert Scarf), which became the pioneering road map for the next forty years of research in this area. One of the outgrowths of this research was development of the field of supply-chain management,…  See more details below

Overview


In 1958, Stanford University Press published Studies in the Mathematical Theory of Inventory and Production (edited by Kenneth J. Arrow, Samuel Karlin, and Herbert Scarf), which became the pioneering road map for the next forty years of research in this area. One of the outgrowths of this research was development of the field of supply-chain management, which deals with the ways organizations can achieve competitive advantage by coordinating the activities involved in creating products—including designing, procuring, transforming, moving, storing, selling, providing after-sales service, and recycling. Following in this tradition, Foundations of Stochastic Inventory Theory has a dual purpose, serving as an advanced textbook designed to prepare doctoral students to do research on the mathematical foundations of inventory theory and as a reference work for those already engaged in such research.

The author begins by presenting two basic inventory models: the economic order quantity model, which deals with "cycle stocks," and the newsvendor model, which deals with "safety stocks." He then describes foundational concepts, methods, and tools that prepare the reader to analyze inventory problems in which uncertainty plays a key role. Dynamic optimization is an important part of this preparation, which emphasizes insights gained from studying the role of uncertainty, rather than focusing on the derivation of numerical solutions and algorithms (with the exception of two chapters on computational issues in infinite-horizon models).

All fourteen chapters in the book, and four of the five appendixes, conclude with exercises that either solidify or extend the concepts introduced. Some of these exercises have served as Ph.D. qualifying examination questions in the Operations, Information, and Technology area of the Stanford Graduate School of Business.

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Product Details

ISBN-13:
9780804743990
Publisher:
Stanford University Press
Publication date:
08/28/2002
Edition description:
1
Pages:
320
Sales rank:
1,161,842
Product dimensions:
6.38(w) x 9.25(h) x 0.90(d)

Table of Contents

Preface
Conventions
1Two Basic Models1
2Recursion27
3Finite-Horizon Markov Decision Processes41
4Characterizing the Optimal Policy57
5Finite-Horizon Theory77
6Myopic Policies91
7Dynamic Inventory Models103
8Monotone Optimal Policies119
9Structured Probability Distributions133
10Empirical Bayesian Inventory Models151
11Infinite-Horizon Theory167
12Bounds and Successive Approximations181
13Computational Markov Decision Processes193
14A Continuous Time Model209
App. AConvexity223
App. BDuality241
App. CDiscounted Average Value261
App. DPreference Theory and Stochastic Dominance279
Index293

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