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Gurobi Solver: Download, Pricing & Documentation

Gurobi’s outstanding performance has been demonstrated through leadership in public benchmark tests and dramatic improvement in solve times year after year. Built from the ground up using the latest developments & techniques, Gurobi’s extremely robust code ensures numerical stability, correctness of results, and scalability. 

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AMPL Brings You the Power of Gurobi

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About Gurobi Optimization

Developer: Gurobi Optimization, Inc.

Current version: 11.0

Gurobi Optimization, founded in 2008, is a renowned company specializing in the development of advanced linear programming (LP), mixed-integer linear programming (MILP), and other related optimization software. Its flagship product, the Gurobi Optimizer, is highly regarded for its exceptional speed, robustness, and the capacity to solve large-scale optimization problems efficiently. Gurobi is the brainchild of Dr. Robert Bixby, Dr. Edward Rothberg, and Dr. Zonghao Gu, each bringing extensive experience in the field of optimization. They collectively sought to create a high-performance solver that could not only address the growing demands of complex data-driven decision-making but also be easily integrable with various programming languages and platforms. This adaptability has made Gurobi a preferred choice in numerous industries, including logistics, finance, energy, telecommunications, and manufacturing. Over the years, Gurobi has continuously evolved, integrating cutting-edge research and algorithms to maintain its position at the forefront of optimization technology, offering both on-premise and cloud-based solutions. Its commitment to innovation, coupled with strong customer support and community engagement, underscores Gurobi’s role as a key player in advancing the field of mathematical optimization.

Problem types supported

Linear and quadratic optimization in continuous and integer variables with high-level constraints such as min/max, and/or, as well as nonlinear functions via piecewise-linear approximation.

Special forms detected

Convex and non-convex quadratic expressions in objectives and constraints; conic quadratic constraints; indicator constraints.

Algorithms available

For continuous problems, primal and dual simplex, interior-point (barrier); for integer problems, advanced branch-and-bound with presolve, feasibility heuristics and cut generators.

Special features

Global optimization of non-convex quadratic problems. Shared-memory parallel processing for barrier, branch-and-bound. Distributed concurrent optimization and tuning to leverage multiple machines. Streamlined access to cloud services. Special facilities for multi-objective optimization and infeasibility diagnosis.

Download Gurobi for All Platforms - Windows, Linux, macOS

Experience the power of Gurobi on the AMPL Portal, available for Windows, Linux, and macOS. 
Gurobi can be used with AMPL from various programming languages using our APIs
Python Logo For Python enthusiasts, Gurobi is also accessible as a module with amplpy, blending seamlessly with your Python projects. Explore more about this integration at AMPL Python Integration.

# Install Python API for AMPL

$ python -m pip install amplpy

# Install Gurobi

$ python -m amplpy.modules install gurobi

AMPL and Gurobi Pricing

Buy Gurobi individually - or combine with AMPL for a full optimization system

INDIVIDUAL

Best for individuals running on one machine

AMPL Pricing

$3,000 /year

Gurobi Pricing

SINGLE-PROCESS

Best for small applications running one process at a time

AMPL Pricing

$4,500 /year

Gurobi Pricing

MULTI-PROCESS

Best for large teams or applications to run multiple processes simultaneously

AMPL Pricing

$7,000 /year

+$700 /additional CPU

Gurobi Pricing

Try it before you buy it

Get a free, full-featured AMPL license, with all solvers, to experience the performance, support, and flexibility we provide as part of our product offering.

INDIVIDUAL

Best for individuals running on one machine

AMPL Pricing

$6,000 /purchase
+ $1,200 maintenance annually

Gurobi Pricing

SINGLE-PROCESS

Best for small applications running one process at a time

AMPL Pricing

$9,000 /purchase
+ $1,800 maintenance annually

Gurobi Pricing

MULTI-PROCESS

Best for large teams or applications to run multiple processes simultaneously

AMPL Pricing

$14,000 /purchase
+ $2,400 maintenance annually

+1,400 /additional CPU

Gurobi Pricing

Try it before you buy it

Get a free, full-featured AMPL license, with all solvers, to experience the performance, support, and flexibility we provide as part of our product offering.

INDIVIDUAL

SINGLE-PROCESS

MULTI-PROCESS

Dynamic License Validation Available (License server)

Works seamlessly in containerized cloud environments
Static License Validation Available (Machine fingerprinted)
Works in air-gapped high security environments
# of Users
1 (Named user)
Unlimited
Unlimited
# of Processes
Unlimited
1
Unlimited
# of Machines
1 Machine at a time (Dynamic)
1 Fixed machine (Static)
1 Machine at a time (Dynamic)
1 Fixed machine (Static)
Multiple machines (Dynamic – not to exceed total core count)
1 Fixed machine (Static)
# of Variables/Constraints
Unlimited
Unlimited
Unlimited
CPUs or vCPUs
8 (16 threads)

16 (32 threads)

8 (16 threads)
(Additional cores can be purchased)
Looking for something…more?

Contact us for customized licenses tailored for your teams specific needs

Gurobi and AMPL Pricing

Buy Gurobi individually - or combine with AMPL for a full optimization system

INDIVIDUAL

Best for individuals running on one machine

AMPL Pricing

$3,000 /yearly subscription

or

$6,000 /purchase
+ $1,200 maintenance annually

Gurobi Pricing

SINGLE-PROCESS

Best for small applications running one process at a time

AMPL Pricing

$4,500 /yearly subscription

or

$9,000 /purchase
+ $1,800 maintenance annually

Gurobi Pricing

MULTI-PROCESS

Best for large teams or applications to run multiple processes simultaneously

AMPL Pricing

$7,000 /yearly subscription
+ $700 additional CPU

or

$14,000 /purchase
+ $2,800 maintenance annually

+ $1,400 additional CPU

Gurobi Pricing

Synergy in Solving: The AMPL-Gurobi Connection

Our enhanced Gurobi driver (previously know as x-gurobi) is now the default gurobi driver. The new driver provides significantly extended modeling support for logical and nonlinear operators natively through Gurobi’s built-in “general constraints” and through linearizations performed by the MP interface.

Gurobi Optimization and AMPL have formed a synergistic partnership, leveraging their respective strengths to provide comprehensive solutions in the realm of mathematical optimization. AMPL, a powerful and flexible algebraic modeling language, is known for its ability to concisely represent complex optimization problems. When integrated with Gurobi’s high-performance optimization solvers, this combination becomes a potent tool for tackling a wide array of challenging computational tasks. The integration allows users to model their optimization problems using AMPL’s user-friendly syntax and then solve them using Gurobi’s advanced algorithms, which are capable of efficiently handling large-scale, complex problems. 

This partnership is particularly beneficial for industries requiring precise and optimal decision-making capabilities, such as supply chain management, logistics, finance, and energy. The seamless interaction between AMPL’s modeling prowess and Gurobi’s solving efficiency creates a robust platform for users who need to formulate and solve optimization problems rapidly and accurately. This collaboration highlights the commitment of both companies to advancing the field of optimization and providing users with tools that are both powerful and accessible, thus enabling better, data-driven decision-making across various sectors.

Real-World Applications for Gurobi

Energy Sector

In the energy and utilities sector, the Gurobi solver plays a crucial role in optimizing various complex operations, significantly enhancing efficiency and sustainability. One of the key applications is in the optimization of power generation and distribution. This includes the scheduling of power plants to meet fluctuating energy demands while minimizing fuel costs and adhering to environmental regulations. Gurobi helps in integrating renewable energy sources like wind and solar power into the grid, balancing the intermittent nature of these sources with demand. Additionally, it’s used for optimizing the maintenance schedules of power plants and distribution networks to ensure reliability and minimize downtime. 

AMPL in Enterprise supports the work of industries such as renewable energy - Picture shows wind turbines in green field.

The users of Gurobi in this sector are typically operations research analysts, electrical engineers, and energy managers who are responsible for ensuring optimal energy production, distribution, and efficient use of resources.

Another important application in this sector is in the optimization of gas and water distribution networks. Gurobi helps in planning and operating these networks, ensuring efficient flow and reducing losses. It can also be used for demand forecasting, helping utilities to predict consumption patterns and adjust their operations accordingly. This aspect of optimization is particularly crucial in times of peak demand or during emergency situations, where the efficient distribution of resources can have significant impacts. 

The roles that commonly use Gurobi for these purposes include network engineers, utility planners, and environmental analysts, who focus on optimizing network performance while considering economic and environmental factors.

Learn more about how Gurobi is being used in combination with AI and machine learning programs >

Finance and Banking

In finance and banking, Gurobi provides sophisticated tools for a range of optimization problems, notably in portfolio optimization and risk management. Portfolio managers use Gurobi to construct investment portfolios that maximize returns while controlling for risk. This involves solving complex mixed-integer linear programming problems to determine the optimal mix of assets. Gurobi’s solver is capable of handling the large, complex datasets typical in financial markets, providing solutions that take into account various constraints and objectives, such as liquidity requirements, regulatory constraints, and market impact costs. 

View of city skyline at sunset - example of places where research is conducted

Risk managers also use Gurobi to model and mitigate financial risks. This includes credit risk modeling, where Gurobi helps in optimizing credit portfolios by assessing the risk of defaults and balancing them against expected returns.

Another significant application in this sector is in asset and liability management (ALM), where financial institutions use Gurobi to match their assets and liabilities in a way that minimizes risk and maximizes profitability. This includes interest rate risk management, currency risk management, and ensuring regulatory compliance. Gurobi is also employed in algorithmic trading, where it’s used to develop strategies that respond to real-time market conditions to maximize trading profits. 

The roles utilizing Gurobi in these contexts include financial analysts, quantitative analysts, and asset managers. These professionals rely on Gurobi’s robust optimization capabilities to make data-driven decisions in a fast-paced and ever-changing financial landscape, where accuracy and speed are critical.

Frequently Asked Questions

Gurobi is designed to solve various types of mathematical optimization problems, including Linear Programming (LP), Mixed-Integer Linear Programming (MILP), Quadratic Programming (QP), Mixed-Integer Quadratic Programming (MIQP), and Mixed-Integer Nonlinear Programming (MINLP). It is highly effective in handling large-scale, complex optimization problems across different industries.

Learn more about Gurobi with our training notebooks and it’s applications with mixed integer programming (learn more here).

Combining AMPL’s modeling simplicity with Gurobi’s powerful optimization engine creates an ideal environment for newcomers to optimization. AMPL’s intuitive modeling language allows users to express optimization problems naturally and concisely, which is particularly beneficial for those just starting out. This simplicity, paired with Gurobi’s extensive range of interfaces supporting popular programming languages like Python, C++, Java, .NET, and MATLAB, opens up accessibility to a wider audience. While beginners might find optimization challenging initially, the joint use of AMPL and Gurobi eases this learning curve. Both offer comprehensive documentation, illustrative examples, and vibrant user communities for support. Furthermore, their commitment to education is evident through the provision of educational licenses and resources, making AMPL and Gurobi a popular combination in academic circles. Together, they provide a more integrated and user-friendly approach to learning and applying optimization.

Learn how to use Gurobi with AMPL.

AMPL and Gurobi are designed to work in tandem, offering a powerful and seamless integration with a wide range of software and systems. AMPL’s strength in model formulation and Gurobi’s robust optimization capabilities complement each other perfectly. This synergy is further enhanced by their support for APIs in several popular programming languages, including Python. This allows users to embed AMPL models directly within custom applications that utilize Gurobi as the solver. This level of flexibility is particularly advantageous in various industrial applications, where they can serve as the core of larger decision-support systems or data analytics platforms. The combination of AMPL’s modeling ease and Gurobi’s optimization strength ensures that users can not only develop solutions efficiently but also integrate these solutions effortlessly with existing systems and workflows, providing a comprehensive and versatile toolset for optimization challenges.

Gurobi is widely used in various sectors for LP and MIP applications. Common uses include supply chain optimization, logistics planning, production scheduling, financial portfolio optimization, and energy distribution. In these applications, Gurobi helps in optimizing resources, minimizing costs, and improving decision-making processes by finding the best possible solutions to complex linear and integer-constrained problems.

Gurobi is designed for high performance and can handle large-scale LP problems efficiently. It utilizes advanced algorithms and techniques such as dual simplex, barrier methods, and concurrent optimization to solve problems quickly. Gurobi’s ability to provide parallel processing also significantly speeds up the solution of large-scale problems by utilizing multiple cores and processors.

While Gurobi is primarily known for linear and mixed-integer linear programming, it can also handle mixed-integer quadratic programming (MIQP) and mixed-integer nonlinear programming (MINLP) to a certain extent. For non-linear constraints, Gurobi can linearize certain types of non-linear functions, enabling the solver to handle a wider range of MIP problems. However, the capability to solve complex non-linear problems might be limited compared to specialized non-linear solvers.

Gurobi provides several features to enhance MIP modeling and solving. This includes advanced presolving to reduce problem size, cutting planes to improve solution bounds, and heuristics for finding good feasible solutions quickly. Gurobi also offers tuning tools to optimize solver parameters for specific problem types, and its branch-and-cut algorithm is highly effective for solving MIPs efficiently.

Gurobi aids decision-making by providing optimal solutions to complex problems in various industries. For instance, in logistics and supply chain management, it helps in route optimization and inventory management. In finance, Gurobi is used for asset allocation and risk management. In manufacturing, it assists in production planning and resource allocation. These solutions help businesses make data-driven decisions, reduce costs, and improve operational efficiency.

Further Information & Resources

Gurobi for AMPL User’s Guide including option descriptions

Gurobi-AMPL interface source code

What’s New in Gurobi 11.0