GAMS/GAMSPy and Snowflake walkthrough
Learn how to connect GAMS and GAMSPy with Snowflake to read model inputs, solve an optimization problem, and write results back to Snowflake.
Optimization Modeling
32 resources
Navigating Trade-Offs: Introducing the GAMS Multi-Objective Optimization (MOO) Framework
Learn how the GAMS Multi-Objective Optimization framework makes it easier to explore trade-offs between competing objectives and generate Pareto fronts without custom implementations.
Embedding machine learning directly into optimization: a real-world stress test
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.
Inside WITCH: Building and Scaling Climate-Economy Models with GAMS
WITCH (World Induced Technical Change Hybrid) is one of the world's leading Integrated Assessment Models, developed by researchers at the RFF-CMCC European Institute on Economics and the Environment (EIEE). Over nearly two decades, it has …
Optimizing Weather Radar Networks for Texas: The Winning GAMSPy Student Competition Fall 2025 Project
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 …
Turning Solver Complexity into Solver Power: The GAMS Advantage
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 …
GAMSPy: Fast and Flexible Optimization in Python
Workshop slides introducing mathematical optimization with GAMSPy, from modeling fundamentals and solver selection to data handling and practical Python workflows.
Unlock the Power of Optimization in Python | GAMSPy Webinar
Discover how to formulate and solve mathematical optimization models in Python with GAMSPy in this webinar and live tutorial from GAMS experts.
Embedding Neural Networks into Optimization Models with GAMSPy
Presentation slides showing how GAMSPy embeds trained neural networks into mathematical optimization models through automated reformulations.
An Introduction to Modelling with GAMSPy
Workshop slides introducing GAMSPy modeling fundamentals, design concepts, Python workflows, solver access, and migration from GAMS to GAMSPy.
Accelerating Carbon Storage Optimization with TotalEnergies
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 …
APG: Optimizing Austria’s Energy Flow
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 …
Optimizing the Perfect Day at Disneyland: The Winning GAMSPy Student Competition Project
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: Optimizing Energy Management
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, …
The Rhodium Climate Outlook
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 …
Why Your Business Needs Optimization
This blog post discusses the necessity of business optimization through the Binary Paintshop Problem, illustrating how businesses can minimize resource usage and improve efficiency by adopting optimization strategies. Using a simple …
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
Introducing GAMSPy
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.
Supercharging GAMS models by linking to Artificial intelligence - Heuristic search and machine learning
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 …
An Overview of Math Programming Solvers
Math programming solvers are the workhorses called upon by GAMS to produce optimal solutions to your mathematical models. This overview provides assistance when you are faced with selecting the correct solver for your particular model.
Optimal Efficient Price Discovery in Dairy Trading Events
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 …
Allocating Out-of-Home Advertising Campaigns
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.
Model Instances with more than 2³¹ Non-Zeros - Impact on Energy Systems Research
With GAMS 37, we now support the generation of model instances with more than 2³¹ non-zeros. We expect huge models to become more important in the future.
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. Renewable fuel policy is complex, and the impacts of policy changes are not always intuitive. Quantitative modeling, as …
Transitioning of a Large Electricity Model into the Amazon Cloud
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 …
USMA
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 …
Dealing with Models that are Unbounded
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 …
Optimizing Power Trading Auctions at 50 Hertz
Supported by several TSOs, the 50Hertz Transmission GmbH, TSO of Eastern Germany and part of the Elia group, manages an internet platform to collect bids and execute described auctions of balancing reserves. A GAMS model helps them match …
Analytik Jena
High Throughput Screening is a scientific experimentation method widely used in pharmaceutical research especially in the field of drug discovery. Because the large number of promising compounds for new drugs cannot be analyzed by manual …
Scaling
Learn how to diagnose and correct numerical scaling problems in GAMS models using scaling attributes, GAMSCHK, CONVERT, and solver diagnostics.
Misbehaving Model – Infeasible
Learn how to diagnose infeasible GAMS models by adding artificial variables, analyzing distorted marginals, and isolating conflicting equations and variable bounds.
DOE
The electricity generation sector in the U.S. is a major contributor of CO2 emissions. Thus emissions reductions from this sector will play a central role in any coordinated CO2 emission reduction effort aimed at combating climate change. …