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See "Nonlinear Optimization and Related Subroutines" for a listing of all NLP subroutines. See Chapter 11, "Nonlinear Optimization Examples," for a description of the inputs to and outputs of all 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 will return missing values.
You can specify the following input arguments with the NLPFEA subroutine:
The following statements call the NLPFEA subroutine with the constraints from the Betts problem (see "Constrained Betts Function" ) and an initial infeasible point x_{0}=(-17,-61). The subroutine returns the feasible point (2,-50) as the vector XFEAS.
proc iml; con = { 2. -50. . ., 50. 50. . ., 10. -1. 1. 10.}; x = {-17. -61}; call nlpfea(xfeas,x,con);
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