10 resources
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.
Presentation slides covering the evolution of CONOPT, recent performance and usability improvements, new APIs, and derivative-based nonlinear optimization workflows.
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 …
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 …
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.
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.
We've got some new links from Pyomo and JuMP to GAMS, which allow efficient interfacing of GAMS with your Pyomo or JuMP models.