The GAMS blog

A Cohort Divisor Application for Schools

Mar 8, 2021 MIRO Examples
A new MIRO application for splitting student groups into cohorts
The new Book by Igancio Grossmann “Advanced Optimization for Process Systems Engineering”

Mar 5, 2021 Book
This new textbook covers both basic and advanced concepts of optimization theory and methods for process systems engineers, combined with a spectrum of exercises and examples using modeling systems like GAMS, to help put knowledge into practice.
A new object oriented MATLAB API

Feb 1, 2021 MATLAB Features
We are happy to announce our new object oriented MATLAB API.
Football Manager Optimizer

Jan 25, 2021 MIRO Examples Knapsack
Are you looking for a tool to improve your soccer manager skills? The new MIRO app “Football Manager Optimizer” could be what you’ve been looking for!
NEOS now requires a valid email address

Jan 18, 2021 NEOS Issue
There is a temporary issue with submitting jobs to the NEOS server. Please read this if you are affected.
MIRO 1.2 - Improving TIMES MIRO

Nov 16, 2020 MIRO Features
The MIRO Pivot renderer was introduced with MIRO 1.1. The TIMES MIRO app used this tool extensively. With GAMS MIRO 1.2 we have further improved it!
Running large models on NEOS for free

Nov 3, 2020 Features News
GAMS and the packaged solvers impose restrictions with regards to the problem sizes that can be solved with a free demo or community license. For academic users, there is a free alternative to run large models: NEOS server.
The 2020 GOR Award for Diploma and Master Theses

Sep 15, 2020 News
Each year, GAMS donates EUR 500 to each of the three winners of the price for excellent Diploma- and Master Theses. Congratulations to this years winners!
How to use GAMS in Jupyter Notebooks

Aug 21, 2020 Features News
We now provide integration of GAMS in Jupyter Notebook. This post summarizes how to get started.
Dealing with Models that are Unbounded

Jul 6, 2020 Tips McCarl Newsletter
Optimization problems occasionally yield unbounded solutions. To find the cause one can modify the model and solve it to gain information. This is done through the imposition of “artificially” large bounds. Linear programming solvers discover unboundedness when they find a variable which is attractive to make larger, but find that the variable may be increased without limit.

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Authors

Aileen Boehme

Adam Christensen

Bruce McCarl

Clemens Westphal

Evangelos Panos

Fred Fiand

Freddy Proske

George Franco

Julien Harou

Leonard Kunz

Logan Randolph

Lutz Westermann

Mohammed Basheer

Marius Bützler

Michael Bussieck

Renke Kuhlmann

Robin Schuchmann

Steve Dirkse

Stefan Mann