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Recording and slides now available from AMPL-INFORMS Webinar Dec 13, 2023

Teaching, Learning, and Applying Optimization: AMPL’s Intuitive Modeling Meets the Python Ecosystem

The fastest optimization toolchains run AMPL

Find out why thousands of businesses, governments, research centers and educational institutions rely on AMPL to investigate and implement the most demanding large-scale optimization applications. 

Join us LIVE Wednesday, Deember 13th at 12 pm EST for a webinar with INFORMS on optimization with AMPL and Python.

The fastest optimization toolchains run AMPL

Find out why thousands of businesses, governments, research centers and educational institutions rely on AMPL to investigate and implement the most demanding large-scale optimization applications. 

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Developed for practitioners

A fully integrated system of optimization

AMPL has been developed for the real-world modeler who needs to manage all phases of the optimization development cycle without sacrificing computational performance. AMPLs straightforward language lets you formulate optimization models the way you think about them, and makes model logic accessible to your team members.

Connect

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Microsoft SQL

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PostgreSQL

All-New Python Ecosystem

Experience the difference for large-scale optimization

Natural mathematical modeling syntax with natural python integration. Our new python ecosystem allows you to collaborate, ideate, and prototype to build full optimization applications and deploy them to your larger systems. 

Integrate with amplpy

Our amplpy interface allows developers to access the features of AMPL from within Python.

Collaborate and model online

Use Jupyter Notebooks on platforms like Google ColabKaggleGradient, and AWS SageMaker. You can also easily communicate results with your teams through Streamlit.

Circle of logos associated with the AMPL-Python Ecosystem for large-scale optimization

All-New Python Ecosystem

Experience the difference for large-scale optimization

Natural mathematical modeling syntax with natural python integration. Our new python ecosystem allows you to collaborate, ideate, and prototype to build full optimization applications and deploy them to your larger systems. 

Integrate with amplpy

Our amplpy interface allows developers to access the features of AMPL from within Python.

Collaborate and model online

Use Jupyter Notebooks on platforms like Google ColabKaggleGradient, and AWS SageMaker. You can also easily communicate results with your teams through Streamlit.

Why AMPL?

An industry-first approach to optimization

Intuitive modeling

Express models the way you think about them. Change your data or solver without modifying your model. AMPL’s fast interpreter and mature APIs support the most challenging applications’ development, deployment, and maintenance.

Built for size and speed

Process your model and data with lightning speed to generate thousands or millions of variables and constraints. AMPL’s translation routines are tuned to the needs of optimization.

Easy to learn and integrate

Master the AMPL language and system quickly with our introductory materials, examples, and documentation. The AMPL book provides a complete tutorial introduction (and it’s great for teaching, too).

Supported by experts

Count on our team to help you in all stages of application building. Our technical staff provides expert advice on AMPL, solvers, and optimization. Our consulting services can help you build and integrate your models.

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Straightforward, powerful integration

AMPL’s APIs connect modelers and developers

Our comprehensive Application Programming Interface provides an object-oriented callable library that lets you access AMPL models and run AMPL commands from broader applications. Data and results can be exchanged directly and efficiently between AMPL’s model entities and data structures in Python, R, C++, C#, MATLAB, and Java. Deploy AMPL models, embed AMPL in enterprise applications, program complex algorithmic schemes, and more.

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Our comprehensive Application Programming Interface provides an object-oriented callable library that lets you access AMPL models and run AMPL commands from broader applications. Data and results can be exchanged directly and efficiently between AMPL’s model entities and data structures in Python, R, C++, C#, MATLAB, and Java. Deploy AMPL models, embed AMPL in enterprise applications, program complex algorithmic schemes, and more.

Optimization without limitations

Innovative research starts here

Optimization has become a paradigm for an exceedingly diverse variety of problems in all fields of engineering as well as in physical and biological sciences, economics, and management. 

Full-featured AMPL packages, including the most popular solvers, are available for academic research at discounts of 90% of the standard price list. Get our Community Edition to use AMPL for free (*internet connection required) with open-source solvers. AMPL also supports the free-for-research offerings of commercial solvers. 

Women researching in a lab

Optimization without limitations

Innovative research starts here

Women researching in a lab

Optimization has become a paradigm for an exceedingly diverse variety of problems in all fields of engineering as well as in physical and biological sciences, economics, and management. 

Full-featured AMPL packages, including the most popular solvers, are available for academic research at discounts of 90% of the standard price list. Get our Community Edition to use AMPL for free (*internet connection required) with open-source solvers. AMPL also supports the free-for-research offerings of commercial solvers. 

AMPL for Education image teacher with students

Educating the next generation of modelers

We make it simple to learn and teach

AMPLs intuitive syntax, extensive resources allow educators to teach with ease and independent learners to start modeling on their own.

Free, Fullfeatured AMPL and Solvers directly on Google Colab. Use our collection of AMPL models in Jupyter Notebooks to assist your teaching.

Instructors can readily configure and distribute bundles of AMPL and popular solvers. They’re easy to install and operate without limitation throughout the duration of your course.

AMPL for Education image teacher with students

Educating the next generation of modelers

We make it simple to learn and teach

AMPLs intuitive syntax, extensive resources allow educators to teach with ease and independent learners to start modeling on their own.

Free, Fullfeatured AMPL and Solvers directly on Google Colab. Use our collection of AMPL models in Jupyter Notebooks to assist your teaching.

Instructors can readily configure and distribute bundles of AMPL and popular solvers. They’re easy to install and operate without limitation throughout the duration of your course.

Worldwide use

The standard for optimization in industry

AMPL makes building optimization application simple, supportable, and accessible. It’s trusted in energy, finance, supply chain, and just about any sector where success depends on making well-informed decisions in a complex environment. We have users throughout the world in companies, agencies, and organizations of all sizes. 

15,000+

AMPL license deployments worldwide

200+

Corporate and government organizations that optimize with AMPL

500+

Universities that use AMPL for teaching and research

1000+

Research papers that credit AMPL models

Ready to get started?

Get up and running with AMPL in minutes with a free Community Edition license. Or contact us to design a custom package for your project.

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Know what you'll pay

Use a Community Edition license to find the products you need. When you’re ready to purchase, compare all our licensing options for AMPL and commercial solvers. 

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Get the help you need

Get started with our developers’ documentation site with examples and support with data exchange, APIs, and a whole range of AMPL plugins and features. Join the discussion on the forum for direct support from our team.