BEAVERTON, Ore. – February 27, 2024 – Gurobi Optimization, LLC, the leader in decision intelligence technology, recently announced the latest version of its leading mathematical optimization solver, Gurobi Optimizer 11.0. Following the release, customers have reported that the solver is already helping them solve new kinds of real-world optimization problems.

With Gurobi 11.0, users can quickly identify precise, globally optimal solutions to complex nonlinear problems. This advancement marks a significant step forward in solving real-world nonlinear problems with Gurobi.

“Material transformation, blending, and logistics are the foundation of the chemical and petrochemical industries,” said Linlin Yang, Principal Data Scientist at Aimpoint Digital, a Gurobi Alliance Partner. “Modeling these steps relies on nonlinear (and generally non-convex) formulations for accurate representation. The nonlinearity in supply chain optimization, process synthesis, and network design naturally results in MINLPs. We’re excited Gurobi can help our team tackle these problems with the latest MINLP offerings in Gurobi 11.0.”

In addition to the new version’s nonlinear capabilities and speed enhancements, Gurobi 11.0 includes the following new features and enhancements:

  • Dynamic Distributed Tuning: With this key enhancement to Gurobi’s popular tuning tool, teams can now share resources across multiple users and jobs when tuning.
  • Improved Concurrent LP Controls: For both deterministic and non-deterministic LP, users can now select precisely which algorithms should be run in a concurrent fashion.
  • New SolutionTarget Option: A new SolutionTarget setting allows users who do not need an optimal basis to obtain faster solutions to LP problems.
  • SAML Integration: Users can now enjoy centralized user access management and single sign-on (SSO) capabilities through Gurobi’s seamless integration with SAML-based identity management systems, in addition to existing support for LDAP.
  • Cosmos DB Support: Gurobi now supports Microsoft® Azure® Cosmos DB®, in addition to existing support for MongoDB® and Amazon® DocumentDB®, for enhanced flexibility when deploying compute clusters.

“We are thrilled to see the immediate impact Gurobi 11.0 has on solving complex, real-world problems across various industries,” said Duke Perrucci, Gurobi Optimization CEO. “Our commitment to innovation and excellence is unwavering, and we continue to push the boundaries of what is possible in optimization. The success stories from our users, including those tackling nonlinear problems in the chemical and petrochemical sectors, inspire us to keep innovating. Together, we are shaping a future where every decision is optimized for the greatest possible outcome.”

To learn more about Gurobi 11.0, visit


About Aimpoint Digital

Aimpoint Digital is an analytics firm that uses data to solve its clients’ most complex use cases, drive effectiveness across value chain operations, and reshape customer experiences. From the integration of self-service analytics to implementing AI at scale and modernizing infrastructure environments, they operate across transformative domains to improve the performance of organizations. Learn more at


About Gurobi Optimization 

With Gurobi’s decision intelligence technology, customers can make optimal business decisions in seconds. From workforce scheduling and portfolio optimization to supply chain design and everything in between, Gurobi identifies the optimal solution, out of trillions of possibilities.

As the leader in decision intelligence, Gurobi delivers easy-to-integrate, full-featured software and best-in-class support, with an industry-leading 98% customer satisfaction rating.

Founded in 2008, Gurobi has operations across the Americas, Europe, and Asia. Over 2,500 global customers across 40+ industries run on Gurobi, including SAP, Air France, and the National Football League, as well as over 80% of the world’s leading enterprises. For more information, please visit or call +1 713 871 9341.



Nell-Marie Colman
(540) 952 9719
Gurobi Optimization

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