Analysis and Algorithms for Service Parts Supply Chains

  • John A. Muckstadt

About this book

Introduction

Services requiring parts has become a $1.5 trillion business annually worldwide, creating a tremendous incentive to manage the logistics of these parts efficiently by making planning and operational decisions in a rational and rigorous manner. This book provides a broad overview of modeling approaches and solution methodologies for addressing service parts inventory problems found in high-powered technology and aerospace applications. The focus in this work is on the management of high cost, low demand rate service parts found in multi-echelon settings.

This unique book, with its breadth of topics and mathematical treatment, begins by first demonstrating the optimality of an order-up-to policy [or (s-1,s)] in certain environments. This policy is used in the real world and studied throughout the text. The fundamental mathematical building blocks for modeling and solving applications of stochastic process and optimization techniques to service parts management problems are summarized extensively. A wide range of exact and approximate mathematical models of multi-echelon systems is developed and used in practice to estimate future inventory investment and part repair requirements.

The text may be used in a variety of courses for first-year graduate students or senior undergraduates, as well as for practitioners, requiring only a background in stochastic processes and optimization. It will serve as an excellent reference for key mathematical concepts and a guide to modeling a variety of multi-echelon service parts planning and operational problems.

Keywords

Analysis Logistics Stochastic Processes Supply Chains algorithms modeling optimization

Authors and affiliations

  • John A. Muckstadt
    • 1
  1. 1.School of Operations Research and Industrial EngineeringCornell UniversityIthacaUSA

Bibliographic information

  • DOI https://doi.org/10.1007/b138879
  • Copyright Information Springer Science+Business Media Inc. 2005
  • Publisher Name Springer, New York, NY
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-0-387-22715-3
  • Online ISBN 978-0-387-27288-7
  • Series Print ISSN 1431-8598
  • About this book
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