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Beginner
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Quadratic programming in intel math kernal lib

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

https://software.intel.com/en-us/node/471098#7CF8EA20-5C99-4E1D-A8D6-C6225A3F406B

In mathlab, the general solution is

with constrains

Ax<=b           Aeq. x =Beq       lb<=x<<la

https://www.mathworks.com/help/optim/ug/quadprog.html?requestedDomain=www.mathworks.com

Our constrain requirement is minimization subjected to   Ax <= b

 

 

 

 

 

 

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2 Replies
Employee
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Dear customer,

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.  

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Black Belt
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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.

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