Introduction to Management Science, 4e, offers a unique model approach and integrates the use of Excel. Through this approach students are better able to grasp the essential concepts covered in the course and see their utility. Each chapter includes a case study that is meant to show the students a real and interesting application of the topics addressed in that chapter. These cases and related applications cut across all functional areas of business and show how management science techniques apply in the business environment.
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Professor emeritus of operations research at Stanford University. Dr. Hillier is especially known for his classic, award-winning text, Introduction to Operations Research, co-authored with the late Gerald J. Lieberman, which has been translated into well over a dozen languages and is currently in its 8th edition. The 6th edition won honorable mention for the 1995 Lanchester Prize (best English-language publication of any kind in the field) and Dr. Hillier also was awarded the 2004 INFORMS Expository Writing Award for the 8th edition. His other books include The Evaluation of Risky Interrelated Investments, Queueing Tables and Graphs, Introduction to Stochastic Models in Operations Research, and Introduction to Mathematical Programming. He received his BS in industrial engineering and doctorate specializing in operations research and management science from Stanford University. The winner of many awards in high school and college for writing, mathematics, debate, and music, he ranked first in his undergraduate engineering class and was awarded three national fellowships (National Science Foundation, Tau Beta Pi, and Danforth) for graduate study. Dr. Hilliers research has extended into a variety of areas, including integer programming, queueing theory and its application, statistical quality control, and production and operations management. He also has won a major prize for research in capital budgeting.
Chapter 1: Introduction
Chapter 2: Linear Programming: Basic Concepts
Chapter 3: Linear Programming: Formulation and Applications
Chapter 4: The Art of Modeling with Spreadsheets
Chapter 5: What-If Analysis for Linear Programming
Chapter 6: Network Optimization Problems
Chapter 7: Using Binary Integer Programming to Deal with Yes-or-No Decisions
Chapter 8: Nonlinear Programming
Chapter 9: Decision Analysis
Chapter 10: Forecasting
Chapter 11: Queueing Models
Chapter 12: Computer Simulation: Basic Concepts
Chapter 13: Computer Simulation with Crystal Ball
Appendix A: Using the Solver Table
Appendix B: Tips for Using Microsoft Excel for Modeling
Appendix C: Partial Answers to Selected Problems
Supplements on the CD-ROM:
Supplement to Chapter 2: More about the Graphical
Method for Linear Programming
Supplement to Chapter 5: Reduced Costs
Supplement to Chapter 6: Minimum Spanning-Tree Problems
Supplement 1 to Chapter 7: Advanced Formulation
Techniques for Binary Integer Programming
Supplement 2 to Chapter 7: Some Perspectives on
Solving Binary Integer Programming Problems
Supplement to Chapter 9: Decision Criteria
Supplement to Chapter 10: Time-Series Forecasting with CB Predictor
Supplement to Chapter 11: Additional Queueing Models
Supplement to Chapter 12: The Inverse Transformation Method for Generating
Random
Observations
Chapters on the CD-ROM:
Chapter 14: Solution Concepts for Linear Programming
Chapter 15: Transportation and Assignment Problems
Chapter 16: PERT/CPM Models for Project Management
Chapter 17: Goal Programming
Chapter 18: Inventory Management with Known Demand
Chapter 19: Inventory Management with Uncertain Demand
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