Foundations of Stochastic Inventory Theory

Evan Porteus

Published by Stanford University Press 2002

Foundations of Stochastic Inventory Theory

Evan Porteus

https://doi.org/10.1515/9781503619883

Overview
Contents

About this book

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.

Topics

Frontmatter Publicly Available Download PDF	i
About the Author Publicly Available Download PDF	v
Contents Publicly Available Download PDF	ix
Preface Publicly Available Download PDF	xv
Conventions Publicly Available Download PDF	xviii
1 Two Basic Models Requires Authentication Unlicensed Licensed Download PDF	1
2 Recursion Requires Authentication Unlicensed Licensed Download PDF	27
3 Finite-Horizon Markov Decision Processes Requires Authentication Unlicensed Licensed Download PDF	41
4 Characterizing the Optimal Policy Requires Authentication Unlicensed Licensed Download PDF	57
5 Finite-Horizon Theory Requires Authentication Unlicensed Licensed Download PDF	77
6 Myopic Policies Requires Authentication Unlicensed Licensed Download PDF	91
7 Dynamic Inventory Models Requires Authentication Unlicensed Licensed Download PDF	103
8 Monotone Optimal Policies Requires Authentication Unlicensed Licensed Download PDF	119
9 Structured Probability Distributions Requires Authentication Unlicensed Licensed Download PDF	133
10 Empirical Bayesian Inventory Models Requires Authentication Unlicensed Licensed Download PDF	151
11 Infinite-Horizon Theory Requires Authentication Unlicensed Licensed Download PDF	167
12 Bounds and Successive Approximations Requires Authentication Unlicensed Licensed Download PDF	181
13 Computational Markov Decision Processes Requires Authentication Unlicensed Licensed Download PDF	193
14 A Continuous Time Model Requires Authentication Unlicensed Licensed Download PDF	209
Appendix A Convexity Requires Authentication Unlicensed Licensed Download PDF	223
Appendix B Duality Requires Authentication Unlicensed Licensed Download PDF	241
Appendix C Discounted Average Value Requires Authentication Unlicensed Licensed Download PDF	261
Appendix D Preference Theory and Stochastic Dominance Requires Authentication Unlicensed Licensed Download PDF	279
Index Requires Authentication Unlicensed Licensed Download PDF	293

Language: English
Publisher: Stanford University Press
Audience: College/higher education;
Pages
- Main content: 320

eBook

Published: August 9, 2002
ISBN: 9781503619883