The General Algebraic Modeling System (GAMS) is specifically designed for modeling linear, nonlinear and mixed integer optimization problems. The system is especially useful with large, complex problems. GAMS is available for use on personal computers, workstations, mainframes and supercomputers.
GAMS allows the user to concentrate on the modeling problem by making the setup simple. The system takes care of the time-consuming details of the specific machine and system software implementation.
GAMS is especially useful for handling large, complex, one-of-a-kind problems which may require many revisions to establish an accurate model. The system models problems in a highly compact and natural way. The user can change the formulation quickly and easily, can change from one solver to another, and can even convert from linear to nonlinear with little trouble.
GAMS lets the user concentrate on modeling. By eliminating the need to think about purely technical machine-specific problems such as address calculations, storage assignments, subroutine linkage, and input-output and flow control, GAMS increases the time available for conceptualizing and running the model, and analyzing the results. GAMS structures good modeling habits itself by requiring concise and exact specification of entities and relationships. The GAMS language is formally similar to commonly used programming languages. It is therefore familiar to anyone with programming experience.
Using GAMS, data are entered only once in familiar list and table form. Models are described in concise algebraic statements which are easy for both humans and machines to read. Whole sets of closely related constraints are entered in one statement. GAMS automatically generates each constraint equation, and lets the user make exceptions in cases where generality is not desired. Statements in models can be reused without having to change the algebra when other instances of the same or related problems arise. The location and type of errors are pinpointed before a solution is attempted. GAMS handles dynamic models involving time sequences, lags and leads and treatment of temporal endpoints.
GAMS is flexible and powerful. Models are fully portable from one computer platform to another when GAMS is loaded to each platform. GAMS facilitates sensitivity analysis. The user can easily program a model to solve for different values of an element and then generate an output report listing the solution characteristics for each case. Models can be developed and documented simultaneously because GAMS allows the user to include explanatory text as part of the definition of any symbol or equation. GAMS is being enhanced and expanded on a continuing basis. Please inspect the release notes for more details.
A transportation problem from the famous 1963 book by George Dantzig is used to illustrate the usefulness of GAMS. This model is part of the model library which contains many more complete GAMS models.
GAMS model types include LP, MIP, MINLP, and different forms of NLPs. Here is a list of all model types that GAMS supports.