GAMS (General Algebraic Modeling System)

The General Algebraic Modeling System (GAMS) allows domain experts to easily express their optimization problems as compact, self-documenting, and executable code, using a notation close to mathematical notation. Model equations and constraints can be expressed in a very natural way.  

The included model library contains realistic examples from many areas and helps users create productive code in little time, while the included commercial and open source solvers are amongst the best available. GAMS is extremely scalable and can handle huge problems.  APIs to all major programming languages make integration of GAMS into existing IT systems straightforward. We emphasize long-term backward compatibility, to protect customer investments into model development.

End users are domain experts (e.g. economists, electrical engineers), with a good understanding of the optimization problem at hand. Supported optimization problem types are linear, non-linear, mixed-integer, mixed-complementary, and many others. End users do not have to be expert programmers, as GAMS handles a lot of the computer science related difficulties with solving optimization problems automatically.A wide range of applications are supported, but the most common ones are economic equilibrium models, energy systems planning and dispatch models, and logistics models.

GAMS offers two products to interact with GAMS from MATLAB^®: GAMS Transfer MATLAB (formerly GDXMRW) and a GAMS MATLAB object-oriented API.

• GAMS Transfer MATLAB aims to exchange data between GAMS and MATLAB with high efficiency. Data in this context means parameter, variable, or equation values of a GAMS optimization model. In MATLAB the data can be loaded into (or read from) tables, structs, dense or sparse matrices. The API is implemented in a combination of C (MATLAB C Matrix API) and MATLAB classes (as the user interface). 
• The GAMS MATLAB object-oriented API offers even more features to interact with the optimization model than pure data exchange.  These features include starting optimization jobs, setting optimization options, or creating and solving a sequence of similar optimization models efficiently. The GAMS MATLAB object-oriented API is implemented using MATLAB classes.  It internally makes use of the GAMS Java API and leverages the integration of Java in MATLAB.