Practical Management Science
eBook - PDF

Practical Management Science

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

Practical Management Science

About this book

Learn to take full advantage of the power of spreadsheet modeling with PRACTICAL MANAGEMENT SCIENCE, 6E, geared entirely to Excel 2016. This edition uses an active-learning approach and realistic problems with the right amount of theory to ensure you establish a strong foundation. Exercises offer practical, hands-on experience with the methodologies. Examples and problems from finance, marketing, and operations management, and other areas of business illustrate how management science applies to your chosen profession -- and how you can use these skills on the job. The authors emphasize modeling rather than algebraic formulations and memorization of particular models. This edition also includes access to Palisade DecisionTools Suite (BigPicture, @RISK, PrecisionTree, StatTools, TopRank, NeuralTools, and Evolver) as well as SolverTable, for sensitivity analysis on optimization models. Chapters 15-17 are available online via MindTap.

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Yes, you can access Practical Management Science by Wayne Winston, S. Albright in PDF and/or ePUB format, as well as other popular books in Economics & Statistics for Business & Economics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. About the Authors
  3. Brief Contents
  4. Contents
  5. Preface
  6. Chapter 1: Introduction to Modeling
  7. Chapter 2: Introduction to Spreadsheet Modeling
  8. Chapter 3: Introduction to Optimization Modeling
  9. Chapter 4: Linear Programming Models
  10. Chapter 5: Network Models
  11. Chapter 6: Optimization Models with Integer Variables
  12. Chapter 7: Nonlinear Optimization Models
  13. Chapter 8: Evolutionary Solver: An Alternative Optimization Procedure
  14. Chapter 9: Decision Making under Uncertainty
  15. Chapter 10: Introduction to Simulation Modeling
  16. Chapter 11: Simulation Models
  17. Chapter 12: Queueing Models
  18. Chapter 13: Regression and Forecasting Models
  19. Chapter 14: Data Mining
  20. References
  21. Index