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Don’t Go It Alone. Gurobi and Its Partners Provide the Continuum of Support You Need.

While the mathematical optimization field is more than 70 years old, many customers are still learning how to make the most of its capabilities. That’s why, at Gurobi, we have established the Gurobi Alliance partner network—a group of trusted partners who can support you in achieving your optimization goals.

Learn More

Free Udemy Course: Intro to Optimization

Unlock the power of optimized decision-making with this online course developed by Gurobi in partnership with Dr. Joel Sokol, professor at Georgia Tech.

Learn More

Gurobi 12.0 Brings New Performance Improvements, Innovative Nonlinear Capabilities, and Smarter Resource Management

Gurobi 12.0 provides users with expanded nonlinear solving capabilities, faster solving times, and smarter resource management.

Learn More

webinar

Webinar: What’s New in Gurobi 10.0

Event Recap

In this webinar, attendees get a look at Gurobi 10.0. We 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.

Moreover, attendees will learn about new features in Gurobi 10.0 like dashboards for the Cluster Manager, flexible deployment via new capabilities of our Web License Service (WLS), as well as a greatly improved matrix-friendly API for gurobipy.

Finally, we briefly introduce a number of open-source Python GitHub repositories that make it even easier to employ Gurobi. These allow the user to incorporate trained machine learning models into MIP model formulations, to simplify working with pandas data, or to analyze and to find the root cause of a numerical issue in an LP or MIP.

A PDF of the webinar slides can be found here.

Meet the Experts

View Bio

Dr. Tobias Achterberg

Vice President of Research and Development
Gurobi Optimization

Dr. Tobias Achterberg

Vice President of Research and Development
Gurobi Optimization

Dr. Achterberg studied mathematics and computer science at the Technical University of Berlin and the Zuse Institute Berlin. He finished his PhD in mathematics under supervision of Prof. Martin Grötschel in 2007. Dr. Achterberg is the author of SCIP, currently the best academic MIP solver. In addition to numerous publications in scientific journals, he has also received several awards for his dissertation and for SCIP, such as the Beale-Orchard-Hays Prize. From 2006, Dr. Achterberg worked for ILOG/IBM as developer of CPLEX in versions 11 to 12.6. Since 2014 he has been involved as a Senior Developer in the development of the Gurobi Optimizer. In his spare time, Dr. Achterberg likes to play the drums, read books, and play board games. Moreover, he enjoys going to rock and punk rock concerts.

View Bio

Dr. Michel Jaczynski

Senior Director of Cloud and Platform R&D
Gurobi Optimization

Dr. Michel Jaczynski

Senior Director of Cloud and Platform R&D
Gurobi Optimization

Dr. Michel Jaczynski has 20 years of experience building components, frameworks and Cloud-based services for optimization applications. As the Director of Cloud and Platform R&D with Gurobi, he is responsible for the development of the Gurobi Instant Cloud and the system architecture of the Gurobi Compute Server. Prior to his role at Gurobi, he worked at IBM on the decision optimization Cloud services and application frameworks. He also worked for ILOG on integrating optimization with enterprise software and a framework to optimize semiconductor Fabs operations in near real-time. Over these various positions, he demonstrated his commitment to building scalable, efficient and easy-to-use tools for optimization. Dr. Jaczynski holds a Ph.D. in Computer Science from the University of Nice Sophia-Antipolis, France. In his spare time, he practices traditional Shaolin Kung Fu with his daughter and enjoys traveling.

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Webinar: What’s New in Gurobi 10.0

Event Recap

Meet the Experts

Dr. Tobias Achterberg

Dr. Tobias Achterberg

Dr. Michel Jaczynski

Dr. Michel Jaczynski

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