I am a intel fortran commercial user and looking for general Quadratic programming routine, but I was unable to find it in the math library. The existing routines limited to the constrain L1 <= x <<L2. see
In mathlab, the general solution is
Ax<=b Aeq. x =Beq lb<=x<<la
Our constrain requirement is minimization subjected to Ax <= b
There's no QP solver in MKL. But what I feel confused is why you are using non-linear least square solver for QP constraints. The hard constraints are linear.
MKL does not provide routines for general minimization, even for a function of one variable. The TRNLS and TRNLSBC routines can be used for QP with bound constraints, but will not be as efficient as a dedicated QP routine.
See http://plato.asu.edu/sub/pns.html and look for a solver that meets your needs. In particular, consider Gurobi and BPMPD as QP solvers, and Mosek and Knitro as a general optimization package with facilities for solving QP problems.