An introduction to management science: quantitative approaches to decision making

Table of Contents: 1. Introduction. 2. An Introduction to Linear Programming. 3. Linear Programming: Sensitivity Analysis and Interpretation of Solution. 4. Linear Programming Applications in Marketing, Finance, and Operations Management. 5. Advanced Linear Programming Applications. 6. Distribution and Network Models. 7. Integer Linear Programming. 8. Nonlinear Optimization Models. 9. Project Scheduling: PERT/CPM. 10. Inventory Models. 11. Waiting Line Models. 12. Simulation. 13. Decision Analysis. 14. Multicriteria Decisions. 15. Time Series Analysis and Forecasting. 16. Markov Processes. 17. Linear Programming: Simplex Method (on Website). 18. Simplex-Based Sensitivity Analysis and Duality (on Website). 19. Solutions Procedures for Transportation and Assignment Problems (on Website). 20. Minimal Spanning Tree (on Website). 21. Dynamic Programming (on Website).

Methodology is a very difficult part of knowledge. How to teach effectively, how to translate knowledge onto common language, how to keep the point in material selection, etc. etc. Such questions are very good resolved in the evaluated book: "An introduction to management science" 13th Ed. I can compare this edition to the 6th one, and can say that both books can add very important impact to a growth of knowledge. As a professor of management theory, I use this book in my everyday teaching practice. I can find very fresh look at well known problems and solutions. A lot of very good practical examples illustrate the operational research theory and teach practicioners how to use quantitative support of decision making. Some easy Excel examples are good presented even for social science oriented students. Lack of suitable CD with the presented cases and examples solution is the most important weakness of the edition.