PROC NLP: Feasible Starting Point

Feasible Starting Point

Two algorithms are used to obtain a feasible starting point.

When only boundary constraints are specified:
- If the parameter $\text{[math]}$ , $\text{[math]}$ , violates a two-sided boundary constraint (or an equality constraint) $\text{[math]}$ , the parameter is given a new value inside the feasible interval, as follows:
  
  $\text{[math]}$
- If the parameter $\text{[math]}$ , $\text{[math]}$ , violates a one-sided boundary constraint $\text{[math]}$ or $\text{[math]}$ , the parameter is given a new value near the violated boundary, as follows:
  
  $\text{[math]}$
When general linear constraints are specified, the algorithm of Schittkowski and Stoer (1979) computes a feasible point, which may be quite far from a user-specified infeasible point.