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Spreadsheet Modeling and Application - With 2 CDs

Spreadsheet Modeling and Application - With 2 CDs - 05 edition

Spreadsheet Modeling and Application - With 2 CDs - 05 edition

ISBN13: 9780534380328

ISBN10: 0534380328

Spreadsheet Modeling and Application - With 2 CDs by S. Christian Albright and Wayne Winston - ISBN 9780534380328
Edition: 05
Copyright: 2005
Publisher: Brooks/Cole Publishing Co.
International: No
Spreadsheet Modeling and Application - With 2 CDs by S. Christian Albright and Wayne Winston - ISBN 9780534380328

ISBN13: 9780534380328

ISBN10: 0534380328

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Chris Albright and Wayne Winston have brought their hallmark teach-by-example approach to the undergraduate spreadsheet modeling course. Renowned for their other successful texts in operations research/management science, Winston and Albright successfully show how spreadsheets are used in real life to model and analyze real business problems. By modeling problems using spreadsheets from the outset, SPREADSHEET MODELING AND APPLICATIONS prepares future managers for the types of problems they will encounter on the job. Real cases throughout the text further cement this book's status as the most relevant of its kind on the market. This text is also accompanied by Palisade Corporation's professional spreadsheet add-ins, DecisionTools Suite.


  • While most texts begin by modeling problems algebraically, SPREADSHEET MODELING AND APPLICATIONS uses spreadsheet models exclusively to generate a more intuitive understanding of the business problem. This spreadsheet-based approach models the way problems are solved in actual business situations.
  • A proven approach by proven authors, SPREADSHEET MODELING AND APPLICATIONS is the latest offering from best-selling authors Winston and Albright, who are recognized as leaders in the community.
  • Albright and Winston teach by example, using realistic, in-depth examples and case studies to motivate students and demonstrate relevance. Examples and cases are drawn from all facets of business, and appeal to students from all functional areas of the business school, including finance and marketing, as well as operations management.
  • "Where Do the Numbers Come From?" features appear in each chapter. These boxes provide context and encourage students to look beyond numbers crunching by explaining where the input came from and how companies facing the problem posed in the chapter.
  • Sensitivity Analysis is performed as a follow up to most example solutions. Students are encouraged to look beyond the "answer" and develop a contextual understanding of the concepts under discussion.
  • "Business Objectives" accompany examples throughout the book to explicitly demonstrate the relevance of the problem.
  • A list of key management science terms and key Excel terms is included at the end of each chapter for student reference.
  • This text contains professional grade spreadsheet add-ins from Palisade Corporation. Bundled with every copy of the book is the DecisionTools Suite containing @RISK, PrecisionTree, BestFit, TopRank, RISKview, etc., and StatTools. The CD-ROM also contains tutorial videos done by Terence Reilly that guide first-time users through these powerful macros.
  • Excel solutions are available to qualified instructors for all of the problems. These are accompanied by "shells" of all of the solutions that get students started. In addition, a generic grading macro is available.

Table of Contents

Table of Contents


1. Introduction to Modeling.

Introduction. A Waiting Line Example. Modeling Versus Models. The Seven-Step Modeling Process. A Successful Management Science Application. Why Study Management Science? Software Included in This Book. Conclusion.

2. Introductory Spreadsheet Modeling.

Introduction. Basic Spreadsheet Modeling: Concepts and Best Practices. Cost Projections. Breakeven Analysis. Ordering with Quantity Discounts and Demand Uncertainty. Decisions Involving the Time Value of Money. Conclusion. Appendix: Tips for Editing and Documenting Spreadsheets.


3. Introduction to Optimization Modeling.

Introduction. Introduction to Optimization. A Two-Variable Model. Sensitivity Analysis. Properties of Linear Models. Infeasibility and Unboundedness. A Product Mix Model. A Multiperiod Production Model. A Comparison of Algebraic and Spreadsheet Models. A Decision Support System. Conclusion. Appendix: Information on Solvers.

4. Linear Programming Models.

Introduction. Advertising Models. Static Workforce Scheduling Models. Aggregate Planning Models. Blending Models. Production Process Models. Financial Models. Conclusion.

5. Network Models.

Introduction. Transportation Models. Assignment Models. Minimum Cost Network Flow Models. Shortest Path Models. Project Scheduling Models. Conclusion.

6. Linear Optimization Models with Integer Variables.

Introduction. Overview of Optimization with Integer Variables. Capital Budgeting Models. Fixed-Cost Models. Set Covering Models and Location/Assignment Models. Conclusion.

7. Nonlinear Optimization Models.

Introduction. Basic Ideas of Nonlinear Optimization. Pricing Models. Advertising Response and Selection Models. Facility Location Models. Models for Rating Sports Teams. Portfolio Optimization Models. Conclusion.


8. Decision Making Under Uncertainty.

Introduction. Elements of a Decision Analysis. The PrecisionTree Add-In. Bayes' Rule. Multistage Decision Problems. Incorporating Attitudes Toward Risk. Conclusion.

9. Introduction to Simulation Modeling.

Introduction. Real Applications of Simulation. Probability Distributions for Input Variables. Simulation with Built-In Excel Tools. Introduction to @RISK. The Effect of Input Distributions on Results. Conclusion.

10. Simulation Models.

Introduction. Operations Models. Financial Models. Marketing Models. Simulating Games of Chance. Conclusion.

11. Queuing Models.

Introduction. Elements of Queuing Models. The Exponential Distribution. Important Queueing. Relationships. Analytical Queuing Models. Queuing Simulation Models. Conclusion.

12. Regression and Forecasting Models.

Introduction. Overview of Regression Models. Simple Regression Models. Multiple Regression Models. Overview of Time Series Models. Moving Averages Models. Exponential Smoothing Models. Conclusion.