[FOX-Ebook]Optimization Modeling with Spreadsheets, 2nd Edition

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.

Table of Contents

Chapter 1 Introduction to Spreadsheet Models for Optimization
Chapter 2 Linear Programming: Allocation, Covering, and Blending Models
Chapter 3 Linear Programming: Network Models
Chapter 4 Sensitivity Analysis in Linear Programs
Chapter 5 Linear Programming: Data Envelopment Analysis
Chapter 6 Integer Programming: Binary Choice Models
Chapter 7 Integer Programming: Logical Constraints
Chapter 8 Nonlinear Programming
Chapter 9 Heuristic Solutions with the Evolutionary Solver
Appendix A1 Optimization Software and Supplemental Files
Appendix A2 Graphical Methods in Linear Programming
Appendix A3 The Simplex Method
Appendix A4 Stochastic Programming