Overview

Mathematical optimization is a well-established, essential technological tool in the financial services industry. For over 50 years, mathematical optimization technologies have been used by leading companies across the financial services ecosystem (including institutional and consumer banks, wealth management firms, hedge funds, insurance providers, and fintech players) to:

  • Address a wide variety of complex business problems including portfolio optimization, cash management, trade settlement, and asset-liability management.
  • Make optimal, data-driven decisions that deliver improved operational efficiency, profitability, and regulatory compliance as well as reduced risk and costs.

To see how it works, visit Gurobi Finance, our dedicated technical documentation for the finance sector.

The Solver That Does More

Gurobi delivers blazing speeds and advanced features—backed by brilliant innovators and expert support.

  • Unmatched Performance
  • Continuous Innovation
  • Responsive, Expert Support
  • Unmatched Performance
  • Continuous Innovation
  • Responsive, Expert Support
  • Gurobi Optimizer Delivers Unmatched Performance

    Unmatched Performance

    With our powerful algorithms, you can add complexity to your model to better represent the real world, and still solve your model within the available time.

    • The performance gap grows as model size and difficulty increase.
    • Gurobi has a history of making continual improvements across a range of problem types, with a more than 75x speedup on MILP since version 1.1.
    • Gurobi is tuned to optimize performance over a wide range of instances.
    • Gurobi is tested thoroughly for numerical stability and correctness using an internal library of over 10,000 models from industry and academia.
     

  • Gurobi Optimizer Delivers Continuous Innovation

    Continuous Innovation

    Our development team includes the brightest minds in decision-intelligence technology--and they're continually raising the bar in terms of solver speed and functionality.

    • Our code is fundamentally parallel—not sequential code that was parallelized—so you can make the most of parallelism and run sequentially.
    • We go beyond cutting-edge MIP cutting planes, with new classes of cuts you can find only with Gurobi.
    • Our advanced MIP heuristics identify feasible, good quality solutions, fast—where other solvers fall flat.
    • Our barrier algorithms fully exploit the features of the latest computer architectures.
    • Our APIs are lightweight, modern, and intuitive—to minimize your learning curve while maximizing your productivity.

  • Gurobi Optimizer Delivers Responsive, Expert Support

    Responsive, Expert Support

    Our PhD-level experts are here when you need them—ready to provide comprehensive guidance and technical support. They bring deep expertise in working with commercial models and are there to assist you throughout the process of implementing and using Gurobi.

    • Tap into our team’s deep expertise—from implementation to tuning and more.
    • We respond to customer inquiries in hours not days, helping to quickly resolve any issues you’re facing.
    • We can help you fit and adapt your mathematical optimization application to your changing requirements.

Faster Portfolio Optimization Compared to Other Commercial Solvers
1 %

Frequently Asked Questions

  • What is mathematical optimization?

    Mathematical optimization uses the power of math to find the best possible solution to a complex, real-life problem. You input the details of your problem—the goals you want to achieve, the limitations you’re facing, and the variables you control—and the mathematical optimization solver will calculate your optimal set of decisions.

  • What’s a real-world example of mathematical optimization?

    80% of the world’s leading companies use mathematical optimization to make optimal business decisions. For example, Air France uses it to build the most efficient schedule for its entire fleet, in order to save on fuel and operational costs, while reducing delay propagation.

  • What makes mathematical optimization “unbiased”?

    Descriptive and predictive analytics show you what has happened in the past, why it happened, and what’s likely to happen next. But to decide what to do with that information, you need human input—which can introduce bias.

    With mathematical optimization, you receive a decision recommendation based on your goals, constraints, and variables alone. You can, of course, involve human input when it comes to whether or not to act on that recommendation. Or you can bypass human input altogether and automate your decision-making.

Additional Insight

OneChronos: Using Optimization and Combinatorial Auctions to Innovate Modern Trading

 Learn More

Guidance for Your Journey

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Always Free for Academics

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

Try Gurobi for Free

Choose the evaluation license that fits you best, and start working with our Expert Team for technical guidance and support.

Evaluation License
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Academic License
Gurobi supports the teaching and use of optimization within academic institutions. We offer free, full-featured copies of Gurobi for use in class, and for research.
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