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Book Description

Comprehensively teaches the fundamentals of supply chain theory

This book presents the methodology and foundations of supply chain management and also demonstrates how recent developments build upon classic models. The authors focus on strategic, tactical, and operational aspects of supply chain management and cover a broad range of topics from forecasting, inventory management, and facility location to transportation, process flexibility, and auctions. Key mathematical models for optimizing the design, operation, and evaluation of supply chains are presented as well as models currently emerging from the research frontier.

Fundamentals of Supply Chain Theory, Second Edition contains new chapters on transportation (traveling salesman and vehicle routing problems), integrated supply chain models, and applications of supply chain theory. New sections have also been added throughout, on topics including machine learning models for forecasting, conic optimization for facility location, a multi-supplier model for supply uncertainty, and a game-theoretic analysis of auctions. The second edition also contains case studies for each chapter that illustrate the real-world implementation of the models presented. This edition also contains nearly 200 new homework problems, over 60 new worked examples, and over 140 new illustrative figures.

Plentiful teaching supplements are available, including an Instructor’s Manual and PowerPoint slides, as well as MATLAB programming assignments that require students to code algorithms in an effort to provide a deeper understanding of the material.

Ideal as a textbook for upper-undergraduate and graduate-level courses in supply chain management in engineering and business schools, Fundamentals of Supply Chain Theory, Second Edition will also appeal to anyone interested in quantitative approaches for studying supply chains.

Lawrence V. Snyder, PhD, is Professor in the Department of Industrial and Systems Engineering and Co-Director of the Institute for Data, Intelligent Systems, and Computation at Lehigh University. He has written numerous journal articles and tutorials on optimization models for supply chains and other infrastructure systems, with a focus on decision-making under uncertainty.

Zuo-Jun Max Shen, PhD, is Professor in the Department of Industrial Engineering and Operations Research and the Department of Civil and Environmental Engineering at the University of California at Berkeley. He is an INFORMS Fellow and has published and consulted extensively in the areas of integrated supply chain design and management, data driven decision making, and systems optimization.

Table of Contents

  1. Cover
  2. Preface
    1. Goals of This Book
    2. Who Should Read This Book
    3. Organization of This Book
    4. New in the Second Edition
    5. Resources for Instructors
    6. Acknowledgments
  3. Chapter 1: Introduction
    1. 1.1 The Evolution of Supply Chain Theory
    2. 1.2 Definitions and Scope
    3. 1.3 Levels of Decision‐Making in Supply Chain Management
  4. Chapter 2: Forecasting and Demand Modeling
    1. 2.1 Introduction
    2. 2.2 Classical Demand Forecasting Methods
    3. 2.3 ForecastAccuracy
    4. 2.4 Machine Learning in Demand Forecasting
    5. 2.5 Demand Modeling Techniques
    6. 2.6 Bass Diffusion Model
    7. 2.7 Leading Indicator Approach
    8. 2.8 Discrete ChoiceModels
    9. PROBLEMS
  5. Chapter 3: Deterministic Inventory Models
    1. 3.1 Introduction to Inventory Modeling
    2. 3.2 Continuous Review: The Economic Order Quantity Problem
    3. 3.3 Power‐of‐Two Policies
    4. 3.4 The EOQ with Quantity Discounts
    5. 3.5 The EOQ with PlannedBackorders
    6. 3.6 The Economic Production Quantity Model
    7. 3.7 Periodic Review: The Wagner–WhitinModel
    8. PROBLEMS
  6. Chapter 4: Stochastic Inventory Models: PeriodicReview
    1. 4.1 Inventory Policies
    2. 4.2 Demand Processes
    3. 4.3 Periodic Review with Zero Fixed Costs: Base‐Stock Policies
    4. 4.4 Periodic Review with Nonzero Fixed Costs: Policies
    5. 4.5 Policy Optimality
    6. 4.6 Lost Sales
    7. PROBLEMS
  7. Chapter 5: Stochastic Inventory Models: Continuous Review
    1. 5.1 Policies
    2. 5.2 Exact Problem with Continuous Demand Distribution
    3. 5.3 Approximations for Problem with Continuous Distribution
    4. 5.4 Exact Problemwith Continuous Distribution: Properties of Optimal and Q
    5. 5.5 Exact Problem with Discrete Distribution
    6. PROBLEMS
  8. Chapter 6: Multiechelon InventoryModels
    1. 6.1 Introduction
    2. 6.2 Stochastic‐ServiceModels
    3. 6.3 Guaranteed‐ServiceModels
    4. 6.4 Closing Thoughts
    5. PROBLEMS
  9. Chapter 7: Pooling and Flexibility
    1. 7.1 Introduction
    2. 7.2 The Risk‐Pooling Effect
    3. 7.3 Postponement
    4. 7.4 Transshipments
    5. 7.5 Process Flexibility
    6. 7.6 A Process Flexibility Optimization Model
    7. PROBLEMS
  10. Chapter 8: Facility Location Models
    1. 8.1 Introduction
    2. 8.2 The Uncapacitated Fixed‐Charge Location Problem
    3. 8.3 Other Minisum Models
    4. 8.4 Covering Models
    5. 8.5 Other Facility Location Problems
    6. 8.6 Stochastic and Robust Location Models
    7. 8.7 Supply Chain Network Design
    8. PROBLEMS
  11. Chapter 9: Supply Uncertainty
    1. 9.1 Introduction to Supply Uncertainty
    2. 9.2 Inventory Models withDisruptions
    3. 9.3 Inventory Models with YieldUncertainty
    4. 9.4 A MultisupplierModel
    5. 9.5 The Risk‐Diversification Effect
    6. 9.6 A Facility Location Model withDisruptions
    7. PROBLEMS
  12. Chapter 10: The Traveling Salesman Problem
    1. 10.1 Supply Chain Transportation
    2. 10.2 Introduction to the TSP
    3. 10.3 Exact Algorithms for the TSP
    4. 10.4 Construction Heuristics for theTSP
    5. 10.5 Improvement Heuristics for theTSP
    6. 10.6 Bounds and Approximations for the TSP
    7. 10.7 World Records
    8. PROBLEMS
  13. Chapter 11: The Vehicle Routing Problem
    1. 11.1 Introduction to the VRP
    2. 11.2 Exact Algorithms for the VRP
    3. 11.3 Heuristics for the VRP
    4. 11.4 Bounds and Approximations for the VRP
    5. 11.5 Extensions of the VRP
    6. PROBLEMS
  14. Chapter 12: Integrated Supply Chain Models
    1. 12.1 Introduction
    2. 12.2 A Location–InventoryModel
    3. 12.3 A Location–Routing Model
    4. 12.4 An Inventory–Routing Model
    5. PROBLEMS
  15. Chapter 13: The Bullwhip Effect
    1. 13.1 Introduction
    2. 13.2 Proving the Existence of the Bullwhip Effect
    3. 13.3 Reducing the Bullwhip Effect
    4. 13.4 Centralizing Demand Information
    5. PROBLEMS
  16. Chapter 14: Supply Chain Contracts
    1. 14.1 Introduction
    2. 14.2 Introduction to Game Theory
    3. 14.3 Notation
    4. 14.4 Preliminary Analysis
    5. 14.5 The Wholesale Price Contract
    6. 14.6 The Buyback Contract
    7. 14.7 The Revenue Sharing Contract
    8. 14.8 The Quantity Flexibility Contract
    9. PROBLEMS
  17. Chapter 15: Auctions
    1. 15.1 Introduction
    2. 15.2 The English Auction
    3. 15.3 Combinatorial Auctions
    4. 15.4 The Vickrey–Clarke–GrovesAuction
    5. PROBLEMS
  18. Chapter 16: Applications of Supply Chain Theory
    1. 16.1 Introduction
    2. 16.2 Electricity Systems
    3. 16.3 Health Care
    4. 16.4 Public Sector Operations
    5. PROBLEMS
  19. Appendix A: Multiple‐Chapter Problems
    1. PROBLEMS
  20. Appendix B: How to Write Proofs: A Short Guide
    1. B.1 How to Prove Anything
    2. B.2 Types of Things You May Be Asked to Prove
    3. B.3 Proof Techniques
    4. B.4 Other Advice
  21. Appendix C: Helpful Formulas
    1. C.1 Positive and Negative Parts
    2. C.2 Standard Normal Random Variables
    3. C.3 Loss Functions
    4. C.4 Differentiation of Integrals
    5. C.5 Geometric Series
    6. C.6 Normal Distributions in Excel and MATLAB
    7. C.7 Partial Expectations
  22. Appendix D: Integer Optimization Techniques
    1. D.1 Lagrangian Relaxation
    2. D.2 Column Generation
  23. Reference
  24. Subject Index
  25. Author Index
  26. End User License Agreement
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