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Optimization Modeling with Spreadsheets, by Kenneth R. Baker
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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.
- Sales Rank: #168452 in Books
- Published on: 2011-05-24
- Original language: English
- Number of items: 1
- Dimensions: 9.45" h x 1.02" w x 6.40" l, 1.75 pounds
- Binding: Hardcover
- 432 pages
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.
About the Author
Kenneth R. Baker, PhD, is Nathaniel Leverone Professor of Management at the Tuck School of Business and Adjunct Professor of Engineering at Dartmouth College. A Fellow of the Institute for Operations Research and the Management Sciences (INFORMS), Dr. Baker has published extensively in his area of research interest, which include mathematical modeling, spreadsheet engineering, and scheduling. He is coauthor of Principles of Sequencing and Scheduling and Management Science: The Art of Modeling with Spreadsheets, Third Edition, both published by Wiley.
Most helpful customer reviews
10 of 10 people found the following review helpful.
Amazingly Clear
By Travis Neale
Great book! It gives you exactly what you need to know to actually put together a working model on your own. It has enough theory so you understand what you're doing, and a lot of practical application material on how to actually do it. It was my third "modeling" book, but the first one to bridge the gap between theory and application. I attribute this primarily on the author's choice of focusing on showing the models in Excel. The other books I've picked up have tried to maintain a neutrality on what you use to build your model, and they focus on the abstract methods, which are important, but leave you lacking the actual details on how to get it done! And let's face it: Chances are you're going to build your model in Excel and use the Frontline solvers anyway. That being said, I now feel confident enough to take my models out of Excel and plant them in other solvers. Once you build a few, the concepts stick.
1 of 1 people found the following review helpful.
Five Stars
By Amazon Customer
Exactly what I needed at a great price.
1 of 3 people found the following review helpful.
The price is good
By Nmr
Good price comparing to our University book store. Its easy to view the book and the [...] website make things much easier as I can view my book from any computer.
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