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Optimizing Modeling with Spreadsheets (Duxbury Applied Series) - Hardcover

 
9780534494742: Optimizing Modeling with Spreadsheets (Duxbury Applied Series)

Synopsis

Spreadsheet-based introduction to mathematical programming concepts and applications, intended for undergraduate and graduate students in management and engineering. Its emphasis on model building and its focus on formulation principles are key features that reinforce its practical approach. The text also includes a comprehensive tutorial on the use of Excel's Solver, and, at a more advanced level, Frontline Systems Premium Solver.

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Review

1. Introduction to Spreadsheet Modeling for Optimization. Elements of a Model. Spreadsheet Models. A Hierarchy for Analysis. Optimization Software. Using Solver. Summary. Homework. 2. Linear Programming Formulations: Allocation, Covering, and Blending Models. Linear Models. Allocation Models. Blending Models. Modeling Errors in Linear Programming. Summary. Homework. 3. Linear Programming Formulations: Network Models. The Transportation Model. The Assignment Model. The Transshipment Model. Features of Special Network Models. Building Network Models with Balance Equations. General Network Models with Expanding Flows. General Network Models with Transformed Flows. Summary. Homework. 4. Sensitivity Analysis Linear Programs. Sensitivity Analysis Transportation Example. Sensitivity Analysis in the Allocation Example. The Sensitivity Report and the Transportation Example. The Sensitivity Report and the Allocation Example. Degeneracy and Alternative Optima. Patterns in Linear Programming Solutions. Summary. Homework. 5. Linear Programming Formulations: Data Envelopment Analysis. A Graphical Perspective on DEA. An Algebraic Perspective on DEA. A Spreadsheet Model for DEA. Indexing. Finding Reference Sets and HCUs. Assumptions and Limitations of DEA. Summary. Homework. 6. Integer Programming. Using Solver with Integer Requirements. Models with Binary Choice. Models with Qualitative Constraints. The Facility Location Model. The Algorithm for Solving Integer Programs. Summary. Homework. 7. Nonlinear Programming. One-Variable Models. Local Optima and Search for an Optimum. Two-Variable Models. Nonlinear Models with Constraints. Linearizations. Summary. Homework. 8. Heuristic Solutions with the Evolutionary Solver. Features of the Evolutionary Solver. An Illustrative Example: Nonlinear Regression. The Machine-Sequence Problem Revisited. The Traveling Salesperson Problem Revisited. Multi-Machine Scheduling. Two-Dimensional Location. Group Assignment. Summary. Homework. Appendix I. Software. Appendix II. Graphical Methods in Linear Programming. Appendix III. The Simplex Method. Appendix IV. Stochastic Programming.

From the Back Cover

Reflects the latest applied research and features state–of–the–art software for building and solving spreadsheet optimization models

Thoroughly updated to reflect the latest topical and technical advances in the field, Optimization Modeling with Spreadsheets, Second Edition continues to focus on solving real–world optimization problems through the creation of mathematical models and the use of spreadsheets to represent and analyze those models. Developed and extensively classroom–tested by the author, the book features a systematic approach that equips readers with the skills to apply optimization tools effectively without the need to rely on specialized algorithms.

This new edition uses the powerful software package Risk Solver Platform (RSP) for optimization, including its Evolutionary Solver, which employs many recently developed ideas for heuristic programming. The author provides expanded coverage of integer programming and discusses linear and nonlinear programming using a systematic approach that emphasizes the use of spreadsheet–based optimization tools. The Second Edition also features:

  • Classifications for the various problem types, providing the reader with a broad framework for building and recognizing optimization models

  • Network models that allow for a more general form of mass balance

  • A systematic introduction to Data Envelopment Analysis (DEA)

  • The identification of qualitative patterns in order to meaningfully interpret linear programming solutions

  • An introduction to stochastic programming and the use of RSP to solve problems of this type

Additional examples, exercises, and cases have been included throughout, allowing readers to test their comprehension of the material. In addition, a related website features Microsoft Office® Excel files to accompany the figures and data sets in the book.

With its accessible and comprehensive presentation, Optimization Modeling with Spreadsheets, Second Edition is an excellent book for courses on deterministic models, optimization, and spreadsheet modeling at the upper–undergraduate and graduate levels. The book can also serve as a reference for researchers, practitioners, and consultants working in business, engineering, operations research, and management science.

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9780470928639: Optimization Modeling with Spreadsheets

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