NLPSolve Matrix Form

problem := ur+dr, {con1, con4, con5}, seq(w[i] = 0 .. 1, i = 1 .. N):
problem_matrix_form := Optimization:-Convert:-AlgebraicForm:-LPToMatrix(problem):

Optimization:-LPSolve(problem, maximize = true);
Optimization:-LPSolve(problem_matrix_form[2 .. 4], maximize = true);


The above trick-conversion method works for all LP and QP problems
However it does not work on NLP problems. I have attached the workshet

Maple-S.mw

Error, (in Optimization:-NLPSolve) constraints must be specified as a set or list of  procedures

In the above worksheet I have a second-order cone problem that I have solved (sucessfully)
with NLPSolve however the speed is not that great hence I was thinking that I could convert
it to NLP[Matrix fom]. In order to do that I need to understand and see how all the constraints
in matrix-form are passed to the NLPSolver to be able to replicate such a process.

How can I make the above problem_matrix_form[???] method work??

As Acer ponted out such conversion is only used to get a "feeling" for how the problem
should be specified, from there it should be trivial to express it in NLPSolve[Matrix Form]