Language Reference

CALL NLPFEA (xr, x0, blc <, par> ) ;

This subroutine is supported only by the IML procedure.

The NLPFEA subroutine computes feasible points subject to constraints.

See the section Nonlinear Optimization and Related Subroutines for a listing of all NLP subroutines. See Chapter 16 for a description of the arguments of NLP subroutines.

The NLPFEA subroutine tries to compute a point that is feasible subject to a set of boundary and linear constraints. You can specify boundary and linear constraints that define an empty feasible region, in which case the subroutine returns missing values.

You can specify the following input arguments with the NLPFEA subroutine:

The NLPFEA subroutine returns the xr argument. The result is a vector that contains either the n coordinates of a feasible point, which indicates that the subroutine was successful, or missing values, which indicates that the subroutine could not find a feasible point.

The following statements call the NLPFEA subroutine with the constraints from the Betts problem (see the section Constrained Betts Function) and an initial infeasible point . The subroutine returns a feasible point as the vector XFEAS.

con = {  2 -50  .   .,
        50  50  .   .,
        10  -1  1  10};
x = {-17. -61};
call nlpfea(xfeas, x, con);
print xfeas;