An Introduction To Management Science
Quantitative Approaches To Decision Making
Twelfth Edition
David R. Anderson
University of Cincinnati
Dennis J. Sweeney
University of Cincinnati
Thomas A. Williams
Rochester Institute of Technology
R. Kipp Martin
University of Chicago
South-Western Cincinnati, Ohio
Contents
Preface Chapter 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. Introduction An Introduction to Linear Programming Linear Programming: Sensitivity Analysis and Interpretation of Solution Linear Programming Applications in Marketing, Finance and Operations Management Advanced Linear Programming Applications Distribution and Network Models Integer Linear Programming Nonlinear Optimization Models Project Scheduling: PERT/CPM Inventory Models Waiting Line Models Simulation Decision Analysis Multicriteria Decisions Forecasting Markov Processes Linear Programming: Simplex Method Simplex-Based Sensitivity Analysis and Duality Solution Procedures for Transportation and Assignment Problems Minimal Spanning Tree Dynamic Programming
Preface
The purpose of An Introduction to Management Science is to provide students with a sound conceptual understanding of the role management science pays in the decision-making process. The text emphasizes the application of management science by using problem situations to introduce each of the management science concepts and techniques. The book has been specifically designed to meet the needs of nonmathematicians who are studying business and economics.
The Solutions Manual furnishes assistance by identifying learning objectives and providing detailed solutions for all exercises in the text.
Note: The solutions to the case problems are included in the Solutions to Case Problems Manual.
Acknowledgements
We would like to provide a special acknowledgement to Catherine J. Williams for her efforts in preparing the Solutions Manual. We