Event Recap

Highlights and Key Takeaways

This free one day event included informative presentations, training and tips from our experts. Plus, a presentation from our trusted partner, Decision Spot.

See below to browse the slides presented at the event:


  • Hidden Gems: Useful Gurobi Features You May Not Know
    In this session, we review powerful features that are part of the Gurobi Optimizer which can be used to take your applications to the next level. We provide tools to make it easy to incorporate multiple objectives, scenario analysis, nonlinear functions, and more into your optimization models. There are also features like warm starts and variable partitioning that can enhance the solver performance. Learning how to correctly use these features can streamline your modeling efforts and inspire new application ideas.


  • Improving Decision-Making with Practical AI
    Even after implementing advanced planning software, companies often still rely on spreadsheet modeling, institutional knowledge, BI reports, and gut feelings to make many significant decisions regularly. This session dives deep into the limitations of traditional planning methods and unveils opportunities we have uncovered in the supply chain domain in the past.  We’ll explore real-world case studies showcasing how businesses leveraged decision-support solutions and our approach to quickly implement them to unlock significant improvements in their supply chain performance.


  • Performance Tuning
    Application performance is dependent on multiple factors. This session guides the audience through common pitfalls that impact application performance. We will cover tuning opportunities, Gurobi parameters and finish with tuning exercises. Bring your laptops and join in the fun.


  • Advanced Modeling
    This session focuses on advanced modeling features in the Gurobi API. The first part gives a brief introduction about modeling extensions in the Gurobi Python API. The second part covers modeling tools for non-linear and logic functions with a focus on linearization. The third part covers Gurobi’s ability to solve multi-objective optimization problems.

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