GAMS is a high-level modeling system for expressing mathematical programming and optimization models using algebraic notation (as in this example). It consists of a language compiler and a stable of integrated high-performance solvers. GAMS is tailored for complex, large scale modeling applications, and allows you to build large maintainable models that can be adapted quickly to new situations. GAMS is specifically designed for modeling linear, nonlinear and mixed integer optimization problems.
GAMS includes an extensive and diverse portfolio of more than 25 solvers.
- LP/MIP/QCP/MIQCP: CPLEX, GUROBI, MOSEK, XPRESS
- NLP: CONOPT, IPOPTH, KNITRO, MINOS, SNOPT
- MINLP: ALPHAECP, ANTIGONE, BARON, DICOPT, OQNLP, SBB
- Solvers for Mixed Complementarity Problems (MCP), Mathematical Programs with Equilibrium Constraints (MPEC), and Constrained Nonlinear Systems (CNS)
- Free alternatives bundled with every GAMS system (e.g. BONMIN (MINLP), CBC (LP, MIP), COUENNE (MINLP), IPOPT (NLP); for academic licenses also SCIP and SOPLEX
Selecting the solver to use is simple - just change one line of code or adjust one option setting. No need to reimplement anything in order to compare solver performance or see what improvements are possible. Similarly, you can switch easily between model types (e.g. linear and nonlinear), so experimenting with different formulations is easy.
With GAMS, you get one environment for a wide range of model types and solvers.
For further information on GAMS, take a look at our Introduction to GAMS.
To see what a model looks like in GAMS, see this example.
And also feel free to contact us for any questions you might have.