Solver Support - Recommended Books - Management Science and Operations Research

Management Science
and Operations Research Textbooks

There's a lot you can learn from textbooks in the fields of operations research and management science, where the optimization methods used by the Solver were first developed and applied. There are many "classic" optimization problems, for transporting goods, blending materials, scheduling personnel, etc. that are similar across many industries. So it pays to consult books like the ones listed below!

If your first acquaintance with optimization or simulation came from a course in an MBA program (long ago), these books will serve as a refresher. If you're new to optimization or simulation, but serious about learning more, these books are a valuable resource.

Management Science: The Art of Modeling with Spreadsheets, Third Edition, Excel 2010 Update

Powell and Baker, Management Science: The Art of Modeling with Spreadsheets

by Stephen G. Powell and Kenneth R. Baker, published by John Wiley & Sons, ISBN 978-0470530672.

Now in its third edition, Management Science helps business professionals gain the essential skills needed to develop real expertise in business modeling. The biggest change in the text is the conversion of software from Crystal Ball to Risk Solver Platform to reflect changes in the field. More coverage of management science topics has been added. Overall, this book teaches you "best practices" in modeling and spreadsheet engineering, as well as techniques of linear and nonlinear optimization, Monte Carlo simulation, and data analysis using Excel. Additional open-ended case studies that are less structured have also been included along with new exercises. These changes will help business professionals learn how to apply the information in the field. A limited term license for the education version of Risk Solver Platform is available for free download with the textbook. However, this education version has much lower problem size limits than the commercial version.

Spreadsheet Modeling and Decision Analysis:
A Practical Introduction to Management Science, 6th Edition

Ragsdale, Spreadsheet Modeling and Decision Analysis

by Cliff T. Ragsdale, published by South-Western College Publishing. ISBN 978-0538746311.

Cliff Ragsdale's book was first to base all of its optimization examples on the Microsoft Excel Solver, and it has become the best-selling MBA textbook for management science. You'll find a discussion of linear, nonlinear and integer programming; an explanation of sensitivity analysis and how to use the Solver's reports; topics like goal programming and multiobjective optimization; and additional coverage of regression, time series analysis, queuing, project management, decision analysis, and other topics. The 6th Edition uses Risk Solver Platform for its examples. A limited term license for the education version of Risk Solver platform is available for free download with the textbook. However, this education version has much lower problem size limits than the commercial version.

Practical Management Science: Spreadsheet Modeling and Applications, 3rd Edition

Winston, Albright, Practical Management Science

by S. Christian Albright and Wayne L. Winston, published by Duxbury Press. ISBN 978-0534465124.

This textbook, widely used in new MBA courses on management science, provides an extensive introduction covering linear and integer programming, nonlinear optimization, and genetic and evolutionary algorithms using Frontline's Evolutionary Solver, as well as other management science topics. This book is slightly more challenging than Cliff Ragsdale's book, but includes an extensive set of spreadsheet models and a whole chapter on the Evolutionary Solver.  It also includes the Premium Solver for Education on CD-ROM.

Optimization Modeling with Spreadsheets

Winston, Albright, Practical Management Science

by Kenneth Baker, published by Duxbury Press, ISBN 0-534-49474-9.

This book focuses entirely on optimization using Excel and the Premium Solver for Education, which is included on CD-ROM. It covers linear programming, sensitivity analysis, network models, data envelope analysis, and integer programming methods in greater depth than the general management science textbooks; but its coverage of nonlinear optimization and the Evolutionary Solver is at about the same level as the books by Ragsdale and Winston & Albright.

Introduction to Mathematical Programming, 4th Edition

Winston, Albright, Practical Management Science

by Wayne Winston and Munirpallam Venkataramanan, published by Duxbury Press. ISBN 0-534-35964-7.

This book focuses entirely on optimization, at a more technical level than the textbooks described above - including topics in linear algebra, the Simplex method, goal programming, integer programming and the Branch & Bound method, and the differential calculus topics underlying nonlinear optimization. It also includes the Premium Solver for Education on CD-ROM.

Managerial Spreadsheet Modeling and Analysis

Hesse, Managerial Spreadsheet Modeling and Analysis

by Rick Hesse, published by Richard D. Irwin. ISBN 0-256-21530-8.

This "good, but hard to find" book teaches you how to formulate a model from a complex business situation, using a four-step process: Picture and paraphrase, verbal model, algebraic model and spreadsheet model. It covers types of models ranging from simple goal-seeking and unconstrained problems to linear, nonlinear and integer programming problems. And it includes over 100 Microsoft Excel 5.0 spreadsheets, covering a wide range of both deterministic and stochastic models.

Model Building in Mathematical Programming, 4th Edition

Williams, Model Building in Mathematical Programming

By H.P. Williams, published by John Wiley. ISBN 0-471-99788-9

Though it doesn't cover spread­sheet optimization, this book is still valuable for its explanation of model-building approaches, especially if you are building larger-scale optimization models. It provides an in-depth treatment of modeling for linear and integer programming problems.   It mentions nonlinear models only briefly, but it offers a unique treatment of large-scale model structure and decomposition methods. It also includes a complete discussion of 24 models drawn from various industries.  The 4th Edition was issued in October 1999.

Introductory Management Science: Decision Modeling with Spreadsheets

Eppen, Gould, Introductory Management Science

by G.D. Eppen, F.J. Gould, C.P. Schmidt, Jeffrey H. Moore, and Larry R. Weatherford, published by Prentice-Hall. ISBN 0-13-889395-0.

The latest version (5th Edition, 1998) of a management science classic, this modern textbook covers linear, integer and nonlinear optimization, Monte Carlo simulation, decision analysis, queuing, forecasting and project management, all from an Excel spreadsheet perspective. Also included is GLP, a graphic tool that lets you visualize the feasible region in linear programming problems.

The Science of Decision-Making: A Problem-Based Approach Using Excel

Denardo, The Science of Decision-Making

by Eric V. Denardo, published by John Wiley. ISBN 0-471-31827-2.

This book focuses on models for decision-making, in deterministic (certain) and stochastic (uncertain) settings.  The first and last sections of the book cover linear programming and integer programming extensively, but not nonlinear or nonsmooth optimization.  The middle sections cover probability, utility theory and decision trees, Markov chains, queuing and simulation.  This book includes a good discussion of basic Excel use and spreadsheet model design -- useful for readers who are not highly experienced with Microsoft Excel. 

Operations Research: Applications and Algorithms, Third Edition

Winston, Operations Research, Applications and Algorithms

by Wayne L. Winston, published by Duxbury Press. ISBN 0-534-52020-0 (with Windows software), 0-534-20973-4 (with Mac software). This popular textbook, also written before the advent of spreadsheet optimizers, covers many classic optimization problems and also includes a discussion of some of the algorithms used in the Solver, such as the Simplex method for linear programming, the Branch & Bound method for integer programming, and selected methods for nonlinear programming -- as well as many other topics in operations research.

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