Spreadsheet Modeling and Decision Analysis (with Microsoft PRJ 2003) / Edition 4

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Overview

Cliff Ragsdale is an innovator of the spreadsheet teaching revolution and is highly regarded in the field of management science. The 4th edition retains the elements and philosophy that has made its past editions so successful. New topics have been added as well as examples that are relevant to decision making in today's business world. This new edition of Spreadsheet Modeling and Decision Analysis provides succinct instruction in the most commonly used management science techniques and shows how these tools can be implemented using the most current version of Microsoft Excel for Windows. This text also focuses on developing both algebraic and spreadsheet modeling skills.

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Editorial Reviews

Booknews
A text/CD-ROM package providing an introduction to the most commonly used management science techniques, showing how these tools can be implemented using Microsoft Excel. Unique features include use of algebraic formulations and spreadsheets together to develop conceptual thinking, emphasis on model formulation and interpretation rather than algorithms, and realistic examples with step-by-step instructions. Includes chapter questions, problems, and cases. The CD-ROMs contain trial and full versions of software, plus spreadsheet files. This edition offers new discussions of data envelopment analysis, genetic algorithms, simulation, and sensitivity analysis techniques. For students familiar with basic Windows and spreadsheet concepts. The author is affiliated with Georgia Southern University. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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Product Details

  • ISBN-13: 9780324321777
  • Publisher: Cengage Learning
  • Publication date: 8/6/2004
  • Edition description: Older Edition
  • Edition number: 4
  • Pages: 800
  • Product dimensions: 8.10 (w) x 10.30 (h) x 1.50 (d)

Meet the Author

Cliff Ragsdale is the Bank of America Professor, Department of Business Information Technology in the Pamplin College of Business at Virginia Tech, where he has taught since 1990. He received his Ph.D. in Management Science and Information Technology from the University of Georgia. He also holds an M.B.A. in Finance and B.A. in Psychology from the University of Central Florida. Before pursuing his Ph.D., he was supervisor of Benefit Finance & Qualified Plans at the international headquarters of Red Lobster, Inc. He is a member consultant for Compass Modeling, Inc., and has served as an information systems and statistical consultant for the General Mills Restaurant Group and the accounting firm of Deloitte & Touche. Dr. Ragsdale's primary areas of research interest include microcomputer systems and applications, artificial intelligence, mathematical programming, and applied statistics. His research has appeared in DECISION SCIENCES, NAVAL RESEARCH LOGISTICS, OMEGA: THE INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, COMPUTERS & OPERATIONS RESEARCH, OPERATIONS RESEARCH LETTERS, PERSONAL FINANCIAL PLANNING, and other publications. He has also received the Pamplin award for excellence in teaching from the Pamplin College of Business Administration at Virginia Tech. Dr. Ragsdale is an active member of DSI and INFORMS. He was proceedings coordinator for the 1995 National DSI Meeting and has served as vice president for Member Services and vice president of Publications for Southeast DSI. He has also served on the board of directors for the Southwest Virginia Chapter of APICS and as the faculty adviser for the student chapter of APICS at Virginia Tech.

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Table of Contents

1. Introduction to Modeling and Decision Analysis 2. Introduction to Optimization and Linear Programming 3. Modeling and Solving LP Problems in a Spreadsheet 4. Sensitivity Analysis and The Simplex Method 5. Network Modeling 6. Integer Linear Programming 7. Goal Programming and Multiple Objective Optimization 8. Nonlinear Programming 9. Regression Analysis 10. Discriminant Analysis 11. Time-Series Analysis 12. Simulation 13. Queuing Theory 14. Project Management 15. Decision Analysis

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