hidden

Start Solving a Different Class of Problems

As a data scientist, your curiosity, diligence, and creativity drive you to extract immense value from your data and models. But what if you could generate optimized decision recommendations, based on your predicted future—to directly influencing business decision-making? With Gurobi, you can.

The World’s Leading Enterprises Optimize with Gurobi

Insight for Data Scientists

Explore these specially curated content pieces. 

Resource > Whitepaper
Combining Predictive and Prescriptive Analytics

By adding prescriptive analytics to your data analytics toolbox, you can go beyond predictions—to optimized decisions.

 Learn More
Resource > Whitepaper
Optimize Your Business Today, While Preparing for a Quantum Future

With decision intelligence technology, you can achieve quantum outcomes, without the wait.

 Learn More
Event
Energy Innovation Summit - Optimization Strategies for the Energy Transition

 Learn More
Event
Gurobi Days India

Gurobi Days is returning to India on April 3 - 4, 2024 for the second consecutive year! We hope you’ll join us at the beautiful Shangri-La Bengaluru!

 Learn More
Resource > Blog
Experience the Power of Mathematical Optimization

Try our optimization application demos to see how quickly Gurobi solves complex real-world problems.

 Learn More
Resource > Brochure
What's New in Gurobi 11.0

Experience global nonlinear solving, speed enhancements, dynamic distributed tuning, and enterprise features.

 Learn More
Resource > Blog
Recommended Books, Blogs, and More

Enrich your understanding of mathematical optimization and its real-world applications.

 Learn More
Resource > Report
Go Beyond Machine Learning and Leverage Other AI Approaches.

Machine learning does not always provide optimal results. Data and analytics leaders should go beyond machine learning and leverage additional AI techniques to solve a wider range of business problems more efficiently.

 Learn More

Open-Source Projects

We believe optimization has the power to make the world a better place. So we’ve created some innovative, open-source tools that help get optimization into more people’s hands—especially those without prior knowledge of optimization and mathematical modeling.

“We’re aiming to connect the world of data science with the world of optimization. With Gurobi, you can take your machine learning ‘black box’ that’s generating your predictions and plug it directly into your optimization model—enabling you to connect your forecasting with optimization.”
Dr. Tobias Achterberg, Vice President of Research and Development, Gurobi Optimization

  • Gurobi Machine Learning
  • Gurobipy Pandas
  • Gurobi OptiMods
  • Gurobi Machine Learning
  • Gurobipy Pandas
  • Gurobi OptiMods
  • Gurobi Machine Learning

    Gurobi Machine Learning

    With Gurobi Machine Learning—an open-source Python project to embed trained machine learning models directly into Gurobi—data scientists can more easily tap into the power of mathematical optimization.

  • Gurobipy Pandas

    Gurobipy Pandas

    Gurobipy Pandas is our convenient wrapper library to connect pandas with gurobipy. It enables users to efficiently build mathematical optimization models from data stored in DataFrames and Series and extract solutions as pandas objects.

  • Gurobi OptiMods

    Gurobi OptiMods

    Gurobi OptiMods is an open-source Python repository of implemented optimization use cases using Gurobi, each with clear and informative documentation that explains how to use it and the mathematical model behind it.

Frequently Asked Questions

  • Prescriptive Analytics

    • What is prescriptive analytics?

      Prescriptive analytics tools like mathematical optimization help you make decisions based on your real-world business goals (“objectives”) and limitations (“constraints.”) This can be especially useful when you’re facing a business problem with multiple, conflicting goals (such as cutting spending while increasing production) and multiple constraints (such as time, distance, product availability).

      Learn more about prescriptive analytics in our article, “What is Prescriptive Analytics?”

    • What is the difference between predictive analytics and prescriptive analytics?

      Predictive analytics seeks to identify patterns in data to forecast future events, such as predicting cyberattacks or imminent machine failures. Prescriptive analytics, on the other hand, utilizes mathematical modeling to guide decisions based on real-world objectives and constraints, such as minimizing costs or managing raw material inventory.
      While predictive analytics tells you what might happen, prescriptive analytics provides actionable recommendations on how to achieve specific goals, given certain limitations.

      Learn more about the difference in our article, “Predictive Analytics vs. Prescriptive Analytics.”

    • What are some examples of prescriptive analytics in the real world?

      In the real world, prescriptive analytics has diverse applications, including transportation providers like Air France and Uber using it to create optimal routing, staffing, and maintenance plans. Professional sports leagues, such as the National Football League, plan their game schedules using prescriptive analytics. Additionally, manufacturers utilize prescriptive analytics to plan and manage the procurement, production, and distribution of their products, aligning decisions with real-world goals and constraints.

      Learn more about examples in our article, “Examples of Prescriptive Analytics.”

    • Can I improve my machine learning applications by applying optimization?

      Yes! By using machine learning predictions as valuable input for mathematical optimization solutions, or conversely, using mathematical optimization to inform machine learning predictions, you can leverage the problem-solving power of mathematical optimization to enhance machine-learning applications.
      Learn more in our article, “Improving Machine Learning Applications with Prescriptive Analytics.”

    • How can prescriptive and predictive analytics work together?

      Say you were planning a trip. Predictive analytics can predict what you may encounter along your journey (weather, traffic, engine trouble), and prescriptive analytics can, given those predictions, identify the route that best helps you achieve your goals (fastest, cheapest, safest route), given your constraints (time, budget, speed limits).
      Here are some additional examples:

      • Use predictive analytics to predict supply chain issues, and use prescriptive analytics to identify the least costly way to reroute shipments.
      • Use predictive analytics to predict cyberattacks before they happen, and use prescriptive analytics to identify the right investigators based on cost and skill.
      • Use predictive analytics to predict imminent machine failure, and use prescriptive analytics to identify the best time to shut down the production line.
      • Use predictive analytics to predict customer likelihood to buy more with targeted offers, and use prescriptive analytics to identify how many discount coupons to offer, in order to maximize revenue.

      Learn more in our article, “How Can Prescriptive and Predictive Analytics Work Together?”

Get Started Now

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
Get a free, full-featured license of the Gurobi Optimizer to experience the performance, support, benchmarking and tuning services we provide as part of our product offering.
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.
Cloud Trial

Request free trial hours, so you can see how quickly and easily a model can be solved on the cloud.

Search