Management Science: The Art of Modeling with Spreadsheets / Edition 3

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Now in its third edition, Management Science helps business professionals gain the essential skills needed to develop real expertise in business modeling. The biggest change in the text is the conversion of software from Crystal Ball to Risk Solver to reflect changes in the field. More coverage of management science topics has been added. Broader coverage of Excel demonstrates how to create models. Additional open-ended case studies that are less structured have also been included along with new exercises. These changes will help business professionals learn how to apply the information in the field.
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Product Details

  • ISBN-13: 9780470530672
  • Publisher: Wiley
  • Publication date: 10/26/2010
  • Edition description: Older Edition
  • Edition number: 3
  • Pages: 528
  • Product dimensions: 8.70 (w) x 11.00 (h) x 1.00 (d)

Meet the Author

Stephen G. Powell has been Professor of Business Administration at Dartmouth College since 1987. He teaches courses in management science, including the core Decision Science course, and electives in the Art of Modeling and Applications of Simulation. His research interests include modeling production lines and service sector business processes, as well as how novices formulate models and use models in decision making. He is co-author of The Art of Modeling with Spreadsheets, with Ken Baker, and recipient of the 2001 INFORMS Prize for Teaching of OR/MS Practice. He is also working with the Tuck Spreadsheet Engineering Research Project, a three-year project to study how individuals and organizations use spreadsheets and to identify best practices.

Ken Baker is a faculty member at Dartmouth College. He is currently Nathaniel Leverone Professor of Management at the Tuck School of Business and also Adjunct Professor at the Thayer School of Engineering. At Dartmouth, he has taught courses relating to Decision Science, Manufacturing Management, and Environmental Management. Over the years, much of his teaching and research has dealt with Production Planning and Control, and he is widely known for his textbook, Elements of Sequencing and Scheduling, in addition to a variety of technical articles. He has served as Tuck School’s Associate Dean and directed the Tuck School’s management development programs in the manufacturing area. In 2001, he was named a Fellow of INFORMS’ Manufacturing and Service Operations Management (MSOM) Society.

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Table of Contents

Chapter 1: Introduction

Chapter 2: Modeling in a Problem-Solving Framework

Chapter 3: Basic Excel Skills

Chapter 4: Advanced Excel Skills

Chapter 5: Spreadsheet Engineering

Chapter 6: Analysis using Spreadsheets

Chapter 7: Data Analysis for Modeling

Chapter 8: Regression Analysis

Chapter 9: Short-term Forecasting

Chapter 10: Nonlinear Optimization

Chapter 11: Linear Optimization

Chapter 12: Optimization of Network Models

Chapter 13: Integer Optimization

Chapter 14: Optimization of Non-smooth Models

Chapter 15: Decision Analysis

Chapter 16: Monte Carlo Simulation

Chapter 17: Optimization in Simulation

Modeling Cases

Appendix: Basic Probability Concepts

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