Best in class mathematical modeling. Performant, scalable, easy to learn.

model - solve - deploy

🎉 Official Release of GAMSPy 🎉

We are excited to announce the official release of GAMSPy after an extended beta-phase!

Explore the future of algebraic modeling in Python. We encourage everyone to try it out today!

Get started with a simple command:

pip install gamspy

More infos on the GAMSPy product page and for academic users on the academic program page .

Non-academic users please contact sales@gams.com.

The General Algebraic Modeling Language

GAMS 48.5.0 (20 Dec 2024)
Release Notes

Express your optimization problem in our easy to learn, efficient modeling language. Find optimal solutions using world class mathematical solvers.

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Graphical User Interfaces for GAMS Models

GAMS MIRO 2.10.4 (29 Oct 2024)
Release Notes

Develop interactive user interfaces for your GAMS models and deploy them locally or in the cloud. Powerful visualization and analysis features included.

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GAMSPy Python Integration

GAMSPy 1.4.0 (20 Dec 2024)
Release Notes

Leverage the power of GAMS' high performance execution system with the flexible Python language to create complex mathematical models effortlessly directly in Python.

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Scalable Model Deployment

GAMS Engine 24.12.20 (20 Dec 2024)
Release Notes

Solve your models, either on-premises or in the cloud with our Engine SaaS. A highly scalable and reliable option for when things just have to work.

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More than just software

Workshops and Training

Learn from our experts about modeling best practices, data exchange techniques, performance tuning of your models and much more.

Model Development & Improvement

Short on modeling experience? We work with your experts to develop tailor-made decision support solutions. If you already have a working model, often we can help improve performance significantly.

Model Deployment

You have a model and need to roll it out? We can help with deployment and UI development, from 100% local to 100% cloud.

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Case Studies

Cloud-based optimization of Energy Supply-Demand Networks and Investment Decisions

The EIP Energy Investment Planner©️ optimizes energy supply and demand networks and helps in evaluating investment decisions with an interactive web-based user interface.

Optimal Efficient Price Discovery in Dairy Trading Events

Charles River Associates operate their Trading System for Efficient Markets (TSEM™) based on a series of GAMS models and determine reference prices for the global dairy trade.

Allocating Out-of-Home Advertising Campaigns

VIOOH enables media owners to efficiently manage their large panel inventory to satisfy the business requirements of their clients.

Modeling Transportation Carbon Intensity Targets for the EU with GAMS

The ICCT asked GAMS to develop, test, and run a partial equilibrium model of the transportation sector in the EU.

Blog

GAMSPy: High-Performance Optimization in Python

With GAMSPy, you can build your Python optimization models in record time. Learn how offloading computational tasks to GAMS, and leveraging set-based declarative algebraic modeling leads to efficient and high-performance optimization.

Published on 13 Dec 2024

QuSol Project Funded

GAMS, alongside KIT-KASTEL, Infineon, RUB, and FUB, has received BMBF funding for the QuSol project to explore quantum computing for solving industrial optimization challenges. We are thrilled to contribute to this pioneering initiative, which promises to reshape the future of optimization technology and bring quantum computing closer to real-world applications.

Published on 20 Nov 2024

INFORMS Annual Meeting in Seattle

GAMS was happy to be part of this years INFORMS Annual meeting, sharing insights and connecting with the optimization community. We had a fantastic time meeting so many enthusiastic professionals and students, exchanging ideas on how GAMS technology can simplify complex modeling tasks and enhance project workflows.

Published on 28 Oct 2024

GAMS at the OR2024 in Munich

This year’s annual conference of the Operations Research Society of Germany (GOR e.V.) was held in Munich from September 3 to September 6. It focused on “Data, Learning, and Optimization” and featured presentations, discussions, and networking opportunities, including social events like a Bavarian reception and conference dinner.

Published on 09 Sep 2024