Summary: Easy to understand and to the point--and without any jargon--PRACTICAL MANAGEMENT SCIENCE 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'll 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 formulatio
ns and memorization of particular models. The CD-ROMs packaged with every new book include the following useful add-ins: the Palisade Decision Tools Suite (@RISK, StatTools, PrecisionTree, TopRank, and RISKOptimizer); Solver Table, which allows you to do sensitivity analysis; and Premium Solver for Education from Frontline Systems. All of these add-ins have been revised for Excel 2007.
Summary: Easy to understand and to the point--and without any jargon--PRACTICAL MANAGEMENT SCIENCE 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'll 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. The CD-ROMs packaged with every new book include the following useful add-ins: the Palisade Decision Tools Suite (@RISK, StatTools, PrecisionTree, TopRank, and RISKOptimizer); Solver Table, which allows you to do sensitivity analysis; and Premium Solver for Education from Frontline Systems. All of these add-ins have been revised for Excel 2007. ...show less
''Prose is casual and understandable; not stuffy or full of jargon. Problems are realistic and motivating for students, but solvable. Working through problems within a spreadsheet provided by the authors along side text discussion is invaluable for the learning experience.''
View Table of Contents
1. Introduction to Modeling.
2. Introductory Spreadsheet Modeling.
3. Introduction to Optimization Modeling.
4. Linear Programming Models.
5. Network Models.
6. Linear Optimization Models with Integer Variables.
7. Nonlinear Optimization Models.
8. Evolutionary Solver: An Alternative Optimization Procedure.
9. Multi-Objective Decision Making.
10. Decision Making Under Uncertainty.
11. Introduction to Simulation Modeling.
12. Simulation Models.
13. Inventory Models.
14. Queueing Models.
15. Project Scheduling Models.
16. Regression and Forecasting Models.
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