With an emphasis on modeling techniques, Jeremy Shapiro’s MODELING THE SUPPLY CHAIN is the perfect tool for courses in supply chain management or for professional managers who seek better analytical tools for managing their supply chains, information technologists who are responsible for developing and/or maintaining such tools, and consultants who conduct supply chain studies using models. Shapiro examines in detail the roles of data, models, and modeling systems in helping companies improve the management of their supply chains. The focus is on optimization models based on linear and mixed integer programming. The complementary role played by descriptive models in developing data inputs for optimization models is thoroughly reviewed. Using numerous applications, Shapiro clearly illustrates that when properly implemented, these methodologies can create accurate and comprehensive models of great practical value. The book also shows how competitive advantage in supply chain management can be most fully realized by developing and applying optimization modeling systems.
- The Second Edition has roughly twice the number of exercises as the First Edition, including both modeling exercises and discussion questions.
- An enhanced book specific website contains modeling exercises involving data files taken from the book and discussion questions involving white papers. The website also contains hotlinks to other websites organized by parts and chapters where they are relevant.
- Entirely new Chapter 6 (Overview of Descriptive Models) and Chapter 12 (Beyond Supply Chain Optimization to Enterprise Optimization), which is an expanded version of material from the First Edition, examining in detail the integration of supply chain decision making with marketing and corporate financial decision making.
- New information regarding the progress in ERP and e-commerce systems, as well as a section on RFID developments in Chapter 2.
- New approaches for optimizing inventory deployment decisions in strategic supply chain design studies is presented in Chapter 10.
- New material in Chapter 11 discusses modeling approaches and case studies to support supply chain decision making under uncertainty.
- Begins with pedagogical examples of linear and mixed integer programming models and methods for optimizing them. The complementary role of heuristic methods, especially for operational problems, is examined.
- Reviews developments in IT that both promote and require supply chain optimization modeling, and supply chain decision databases are examined in detail.
- Discusses modeling applications to supply chain management problems at all levels of planning, such as strategic, tactical, and operational.
- Surveys descriptive models and methods important to supply chain planning including forecasting, simulation, systems dynamics, activity-based costing, data envelopment analysis, and the balanced scorecard.
- Explains how companies can adapt their business processes to fully achieve integrated supply chain management by the use of modeling systems.
- Provides examples of how concepts from management disciplines can be translated into model elements.
Part I: INTRO TO SUPPLY CHAIN MANAGEMENT AND SUPPORTING INFORMATION TECHNOLOGIES.
1. Supply Chain Management, Integrated Planning, and Models.
2. Information Technology.
Part II: MODELS.
3. Fundamentals of Optimization Models: Linear Programming.
Appendix 3A: The Simplex Method of Linear Programming.
4. Fundamentals of Optimization Models: Mixed Integer Programming.
Appendix 4A: The Branch-and-Bound Method for Mixed Integer Programming.
5. Unified Optimization Methodology for Operational Planning Problems.
Appendix 5A: A Recursive Method for Optimizing Routes.
6. Overview of Descriptive Models.
7. Supply Chain Decision Databases.
Part III: APPLICATIONS.
8. Strategic and Tactical Supply Chain Planning.
9. Operational Supply Chain Planning.
10. Inventory Planning.
11. Supply Chain Decision Making under Uncertainty.
Part IV: THE FUTURE.
12. Beyond Supply Chain Optimization to Enterprise Optimization.
13. Organizational Adaptation to Modeling Systems.
Credits.
Index.
Jeremy F. Shapiro
Jeremy Shapiro is a professor emeritus in the Sloan School of Management at MIT. For nine years he served as the co-director of MIT's Operations Research Center. Previously, he was employed by Procter and Gamble, Hughes Aircraft Company, and the Port of New York Authority. He received his B.M.E. and M.I.E. degrees from Cornell University and a Ph.D. degree in Operations Research from Stanford University.
Dr. Shapiro has published over 60 papers in the areas of operations research, mathematical programming, logistics, supply chain management, finance, and marketing. He is also president of SLIM Technologies, LLC, a Boston-based firm specializing in the implementation and application of modeling systems for supply chain management and other business problems. His outside interests include reading, traveling, biking and playing tennis. He is married to Martha J. Heigham and has three children, Alexander, Lara, and Nicholas.
