'Easy to understand and to the point, MANAGEMENT SCIENCE MODELING, 4th Edition, uses an active-learning approach and realistic problems to help you understand and take advantage of the power of spreadsheet modeling. With real examples and problems drawn from finance, marketing, and operations research, you will easily come to see how management science applies to your chosen profession and how you can use it on the job. The authors emphasize modeling over algebraic formulations and memorization of particular models.
' Given its Excel-based approach and application-oriented material, Excel 2010 updates are key to this edition. All Excel applications, problems, and screen shots are updated to reflect Excel 2010. Old chapters 9 (Multiobjective Decision Making) and 15 (Project Management) are now offered online, and the balance of chapters have been renumbered accordingly. In the first optimization chapter, Chapter 3, the authors replaced the introductory two-variable diet model with a simpler two-variable product mix model. Then they follow it up with a larger version of the same basic product mix model. These revisions should make the introduction to optimization easier for instructors to teach and for students to follow. The authors have updated and refined examples, cases, and problems. This edition also offers pedagogical tools to help students and instructors. More and better exercises have been added to help students grasp concepts. Modeling skills are emphasized through the use of Microsoft® Excel and are incorporated throughout the text. The use of spreadsheets allows students of varying mathematical backgrounds to build skills as they work through sophisticated problems. Interdisciplinary examples and problems from finance, marketing, and operations research?covering topics such as portfolio ion, options, pricing models, and many others?keep student interest at a high level throughout the course.
'1. Introduction to Modeling.2. Introduction to Spreadsheet Modeling.3. Introduction to Optimization Modeling.4. Linear Programming Models.5. Network Models.6. Optimization Models with Integer Variables.7. Nonlinear Optimization Models.8. Evolutionary Solver: An Alternative Optimization Procedure.9. Decision Making Under Uncertainty.10. Introduction to Simulation Modeling.11. Simulation Models.12. Inventory Models.13. Queueing Models.14. Regression and Forecasting Models.15. Project Management (Online only).16. Multiobjective Decision Making (Online only).
'S. Christian Albright: Indiana University, School of Business Wayne L. Winston: Indiana University
