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.
Express your optimization problem in our easy to learn, efficient modeling language. Find optimal solutions using world class mathematical solvers.
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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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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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.
Learn moreLearn from our experts about modeling best practices, data exchange techniques, performance tuning of your models and much more.
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.
You have a model and need to roll it out? We can help with deployment and UI development, from 100% local to 100% cloud.
Contact us at consulting@gams.com to discuss your requirements!
Alpro, a European leader in plant-based food products, faced the challenge of optimizing its factory’s energy management. With the help of our consulting team, the company implemented two custom models and a graphical user interface, streamlining its operational pipeline from data gathering to daily energy trading and consumption.
At the United States Military Academy in West Point, all students must graduate in four years. Each student's daily activities are a carefully regimented balance of academic, military, and physical requirements. The ~4,500 enrolled cadets compile their individual academic programs, which results in challenging scheduling problems.
At INFORMS Analytics+ 2025 in Indianapolis, GAMS showcased its latest advancements—including the Python-native modeling tool GAMSPy—through hands-on workshops and tech demos on embedding machine learning in optimization. The event offered an inspiring mix of technical insights and community connection, reaffirming the power of collaboration in the optimization space.
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.
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.
