37 resources
There's a class of industrial optimization problems that sits just out of reach of classical solvers. The physics-based simulation model exists and is accurate — but it's a numerical black box.
CGE models are powerful tools for policy analysis, but their complexity can limit their reach. This post explains how GAMS MIRO helps turn CGE models into interactive policy platforms for scenario design, comparison, visualization, and …
See which solvers are included with free personal GAMS and GAMSPy licenses and which additional solvers are available to academic GAMSPy users.
GAMS Engine K is our enterprise-grade job and user management system for running GAMS optimization models on Kubernetes. It is built for high-demand environments that require maximum scalability, flexibility, and resilience.
Moving data between environments is a relic of the past; with GAMS and GAMSPy, you can formulate and solve large-scale optimization models without ever duplicating data or leaving your secure environment. Databricks has become the central …
Mathematical optimization drives modern industrial efficiency, but many organizations face a Deployment Gap: the disconnect between a model solved on an engineer’s laptop and a scalable enterprise service.
Update (July 2026): The article has been extended and includes now result from SCIP Concurrent solver. SCIP-Conc is a parallel solver for mixed-integer programming, built on SCIP and has been around for some time. Recent activities for …
We are happy to present the winning project of our GAMSPy Student Competition Fall 2025. Nikhil Trivedi, an undergraduate student from the University of Wisconsin-Madison, took first place with a project that tackles the critical …
A hands-on comparison of ReLU modeling in GAMSPy, MIP vs NLP, for adversarial verification on realistic networks. The workflow, code snippets, and trade-off between speed and guarantees are all explained in details.
Mathematical optimization depends on solvers - yet using them effectively can be daunting. At GAMS, we turn solver complexity into solver power, providing both a unified modeling interface and deep, decades-long expertise in solver …
Workshop slides introducing mathematical optimization with GAMSPy, from modeling fundamentals and solver selection to data handling and practical Python workflows.
Discover how to formulate and solve mathematical optimization models in Python with GAMSPy in this webinar and live tutorial from GAMS experts.
Presentation slides showing how GAMSPy embeds trained neural networks into mathematical optimization models through automated reformulations.
Workshop slides introducing GAMSPy modeling fundamentals, design concepts, Python workflows, solver access, and migration from GAMS to GAMSPy.
Presentation slides covering the evolution of CONOPT, recent performance and usability improvements, new APIs, and derivative-based nonlinear optimization workflows.
For a long time, GPUs were essential for various AI applications and other high-performance compute applications but had limited impact on mathematical optimization. That’s changing.
In the third part of our GAMS MIRO walkthrough, we will fine-tune our application with custom code. We'll show you how to create a custom renderer, widget, and importer/exporter.
In the second part of our GAMS MIRO walkthrough, we will explore all the configuration options available, from changing general settings to defining default views. We'll also demonstrate how to add an interactive dashboard to display our …
In the first part of our GAMS MIRO walkthrough, we will guide you through converting a GAMSPy model into a fully functional web application. We'll also show you how to set up MIRO for rapid prototyping and introduce you to the powerful …
To support their carbon neutrality ambitions, the global energy company TotalEnergies developed a complex optimization model for Carbon Capture and Storage (CCS). This highly sophisticated model, capable of managing the complex CO2 …
The Austrian Power Grid (APG) partnered with our consulting team to optimize its electricity transmission model. As a result, model-solving time was slashed by over 60%, memory usage dropped by 80%, and various infeasibilities were …
We are happy to present the winning project of our 2024/2025 GAMSPy Student Competition. Yiheng Su, a PhD student from the University of Wisconsin-Madison, developed an optimization model to plan the most efficient and enjoyable day at …
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, …
Rhodium Group is a renowned research organization specializing in comprehensive analysis of global trends. With a strong focus on energy, climate, and economic issues, they provide critical insights that inform decision-making at the …
GAMS Transfer R was first released with in August 2022 and has been included in all subsequent GAMS releases. Recently, we made GAMS Transfer R open-source and available on CRAN. In this blog post, we will provide a brief overview of GAMS …
The EIP Energy Investment Planner© optimizes energy supply and demand networks and helps in evaluating investment decisions with an interactive web-based user interface
Over 23 years after its inception, the GDX library is now ported to C++17 and its source code freely available on GitHub. This implicitly documents the layout of the GDX file format and gives everyone the ability to build and maintain their …
Learn how GAMSPy revolutionizes mathematical optimization by seamlessly integrating the power of Python's expressive language with the efficiency of GAMS, offering a streamlined and high-performance solution for complex modeling challenges.
Are you ready to transform your GAMS modeling class with modern tools and streamline grading? In this blog post, our guest author Christophe Gouel from INRAE explains how he adjusted his workflow.
GAMS is good at finding decision variable values that provide the optimal solution to a problem for a given set of scenario parameters. It is more difficult to find a strategy that can test combinations of potentially many parameters in an …
Global Dairy Trade trading event auctions are the leading global online marketplace for trading large volume dairy ingredients and for reference price discovery. The GDT Trading Events and GDT Pulse Auctions are powered by CRA’s Trading …
VIOOH is a leading global digital out of home (OOH) marketplace. Launched in 2018 and with headquarters in London, VIOOH’s platform connects buyers and sellers in a premium marketplace, making OOH easily accessible.
Our new data-centric GAMS Transfer API allows convenient exchange of large data sets between GAMS and Matlab or Python, and uses the native data structures of those platforms. This Python example shows how easy it is to use GAMS Transfer.
Learn how to use GitHub Actions with GAMS Engine to run automated tests for your optimization models.
Stadtwerke München have recently lifted their computationally expensive GAMS model into the cloud. This white paper gives a high level overview of the techniques used and the benefits of a cloud deployment over a traditional on-premise …
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 …
We've got some new links from Pyomo and JuMP to GAMS, which allow efficient interfacing of GAMS with your Pyomo or JuMP models.