Nonlinear program (NLP)

Mathematically, the nonlinear programming (NLP) Problem looks like:

 L < x < U

where

x is a vector of variables that are continuous real numbers;

f(x) is the objective function;

g(x) represents the set of constraints;

á is some mixture of <, = and > operators; and

L and U are vectors of lower and upper bounds on the variables.

Both f and g must be differentiable which prohibits ABS, MIN and MAX functions from appearing.  (They can be included in the DNLP alternative below.)  For information on the names of the solvers that can be used on models in the NLP class see the section on Solver Model type Capabilities.

Note NLP models can possibly have the nonlinear terms inactive and in such a case setting the model attribute TryLinear = 1 causes GAMS to check the model and use the default LP solver if possible.