When facing complex, mission-critical business decisions, it’s your job to examine the data and recommend the best course of action. But when faced with multiple objectives, multiple constraints, and an ever-changing business landscape, how can you be sure you’re making the best recommendations?

That’s why data professionals are adding Gurobi to their analytics toolbox. By combining machine learning with Gurobi, you can explore a universe of possibilities and quickly identify and rank your best-possible courses of action.

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Level 1 (Part 1) – Introduction for Data Scientists

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Level 1 (Part 2) – Introduction for Data Scientists

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  • Lightweight Programming Interfaces
  • Rich Python Modeling Environment
  • Flexible Licensing
  • Multiple Scenario Analysis
  • General Constraints
  • Function Constraints
  • Platform Choice
  • Lightweight Programming Interfaces
  • Rich Python Modeling Environment
  • Flexible Licensing
  • Multiple Scenario Analysis
  • General Constraints
  • Function Constraints
  • Platform Choice
  • Gurobi Optimizer Delivers Lightweight Programming Interfaces

    Lightweight Programming Interfaces

    Integrate Gurobi into your applications easily, using the languages you know best. Our programming interfaces are designed to be lightweight, modern, and intuitive, to minimize your learning curve while maximizing your productivity.

    • Object-oriented interfaces for C++, Java, .NET, and Python
    • Matrix-oriented interfaces for C, MATLAB, and R
    • Links to standard modeling languages: AMPL, GAMS, AIMMS, and MPL
    • Links to Excel through Frontline Solvers

  • Gurobi Optimizer Delivers Rich Python Modeling Environment

    Rich Python Modeling Environment

    Our Python API includes higher-level modeling constructs that make it easier to build optimization models. Choose from Anaconda Python distributions with pre-built libraries to support application development, Spyder for graphical development, and Jupyter for notebook-style development.

    • Python interactive interface for powerful prototyping and quick testing
    • Language extensions for easier coding of a model
    • Documented best practices to get you started quickly
    • Pre-built Python libraries support full application development
    • Python Matrix API for matrix-oriented modeling using NumPy or SciPy matrices

  • Gurobi Optimizer Delivers Flexible Licensing

    Flexible Licensing

    Deploy your model where and how you want. One user can solve a single model on one machine, or many users can solve multiple models using many machines. You can also solve models locally or on an internal or public cloud.

    • Each license can be used for both development and deployment.
    • Each license can run multiple applications.
    • Licenses can be transferred from consulting developer to end user.
    • License grows as chip capabilities grow.

  • Gurobi Optimizer Delivers Multiple Scenario Analysis

    Multiple Scenario Analysis

    Use Gurobi as a “digital twin” for your business—enabling you to explore the business impact of certain decisions or what-if scenarios, before they happen.

  • Gurobi Optimizer Delivers General Constraints

    General Constraints

    By supporting variable relationships directly in the Gurobi API, we simplify the modeling process—performing the transformation to a corresponding MIP formulation automatically and transparently during the solution process.

  • Gurobi Optimizer Delivers Function Constraints

    Function Constraints

    Express common modeling constructs like MIN/MAX, ABS, AND/OR, and IF/THEN at a higher level, making such models easier to build and maintain.

  • Gurobi Optimizer Delivers Platform Choice

    Platform Choice

    Gurobi Optimizer supports a broad range of computing platforms—across Windows, Mac, Linux, and AIX.

Frequently Asked Questions

  • What is Prescriptive vs. Predictive Analytics?

    Prescriptive analytics tools help you make decisions based on your real-world 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).


    Predictive analytics tools seek to find patterns in data, in order to predict what might happen in the future. For example, predictive analytics can predict who will launch which cyberattack, which experiments are more likely to prove the hypothesis, imminent machine failure, supply chain issues, infrastructure maintenance needs, and price movements—all before they happen.

  • What Is an Example of Prescriptive Analysis?

    Although there are countless ways to use prescriptive analytics, here are some real-world examples, with links to their stories:


    • Transportation providers, such as Air France, Swissport, and Uber, use prescriptive analytics to create optimal routing, staffing, and maintenance plans.
    • Professional sports leagues, including the National Football League and Beko BBL, plan their game schedules using prescriptive analytics.
    • Manufacturers use prescriptive analytics to plan and manage the procurement, production, and distribution of their products.
  • What Is the Goal of Prescriptive Analytics?

    Prescriptive analytics tools provide a detailed set of recommendations for how you can best achieve your goals, given your limitations. Although you can use it to automate decision-making, you can use it to inform your traditional decision-making processes. Its ability to explore what-if scenarios can be particularly helpful.

  • How Can Prescriptive Analytics Be Used with Predictive Analytics?

    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.


  • What Is an Advantage of Prescriptive Analytics?

    Prescriptive analytics doesn’t rely on historical data—which means you can make decisions for the future, even when it doesn’t look like your past. To use prescriptive analytics, you need to know three things:


    • The goals you need to achieve (“objectives”)
      • For example:
        • Minimizing product costs
      • The limitations you’re facing (“constraints”)
        • For example:
        • Minimum production of a given product
        • Required manufacturing time and cost of a particular machine
        • Raw material inventory
    • Finished goods inventory capacity
    • The questions you’re asking (“decision variables”)
      • For example:
        • In which order should we produce which products?
        • In which manufacturing facilities?
        • On what product lines?
        • In what quantities?


    With this information, the prescriptive analytics tool can generate a detailed action plan for achieving your goals, given your limitations.

Guidance for Your Journey

Gurobi: Always Free for Academics

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Trusted Partners, at Your Service

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Our global team of helpful, PhD-level experts are here to support you—with responses in hours, not days.

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