Additional Optimization-related Resources

Below are some external resources, including interesting books and blogs you may want to consider as you look to become more familiar/proficient at optimization. You may also be interested in viewing some personalized training options and 3rd party consulting resources. We are also happy to direct you to additional training and consulting resources. Just contact us at your convenience.

eBook: Choosing a Math Programming Solver

In this eBook, we guide you through the step-by-step process of choosing a mathematical programming solver – so that you can find the best solver for your business requirements.




Model Building in Mathematical Programming

H. Paul Williams A great overview and introduction to the process of creating mathematical programming representations of business problems




Model Building in Mathematical Programming

Dimitris Bertsimas, John N. Tsitsiklis, and John Tsitsiklis Information on the algorithms and mathematics underlying the solution of linear programming problems.




Linear Programming: Foundations and Extensions

Robert J. Vanderbei Another resource on the algorithms and mathematics underlying the solution of linear programming problems.




Primal-Dual Interior Point Methods

Stephen J. Wright A detailed treatment of interior-point methods for linear programming.




Integer Programming

Laurence A. Wolsey Information on the algorithms and mathematics underlying the solution of mixed-integer programming problems




Puzzles and Games: A Mathematical Modeling Approach

Tony Hürlimann This book is a comprehensive guide to mathematical modeling. It uses about 100 puzzles as “case studies” and represents them as mathematical models.




Opt Art: From Mathematical Optimization to Visual Design

Robert Bosch A fun and interesting book that uses integer programming models to create art.




The Optimization Edge: Reinventing Decision Making to Maximize All Your  Company’s Assets

Steve Sashihara Provides an executive-friendly explanation of how optimization can boost performance and drive innovation.




Integer Linear Programming in Computational and Systems Biology

Integer linear programming (ILP) is a versatile modeling and optimization technique that is increasingly used in non-traditional ways in biology, with the potential to transform biological computation.




Interesting Blogs

These are a few of the interesting 3rd party blogs we’ve come across. Some are obviously more active than others, and we’ll try to maintain this list over time. If you know of a good, independent OR blog you would like added to the list, please send an email to

Nathan Brixius

-Optimization, Analytics, Software. By Nathan Brixius.

Spaghetti Optimization

-A cookbook about math, algorithms, and programming. By Stefano Gualandi.

Yet Another Math Programming Consultant

-Helping people implement math programming models. By Erwin Kalvelgen.

Punk Rock Operations Research

-Peace, love, and operations research. By Laura McLay.

Michael Trick’s Operations Research Blog

-Thoughts on the world of operations research. By Mike Trick.

The Optimization Edge Blog

-Insights for business executives and advanced analytics practitioners. By Princeton Consultants.

Guidance for Your Journey

Gurobi: Always Free for Academics

We make it easy for students, faculty, and researchers to work with mathematical optimization.

Trusted Partners, at Your Service

When you face complex optimization challenges, you can trust our Gurobi Alliance partners for expert services.

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Our global team of helpful, PhD-level experts are here to support you—with responses in hours, not days.

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Gurobi 10.0 Delivers Blazing-Fast Speed, Innovative Data Science Integration, and an Enterprise Development and Deployment Experience
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Webinar: What’s New in Gurobi 10.0
In this webinar, attendees will get a first look at our upcoming product release, Gurobi 10.0. We will summarize the performance improvements and highlight some of the underlying algorithmic advances, such as the network simplex algorithm, enhancements in concurrent LP, and optimization based bound tightening.
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