Hello,
I've run into the problem that I need to solve an optimization problem for very large matrices. The equality constraint matrix is around 500 (rows) by 12000 (column), There are two other constraints sum-to-unity and non-negativity. The only way I can make such a large matrix is using sparse, but lsqlin/ quadprog constraints (matlab fn) do not cooperate with sparse matrices. Is there some other way I can formulate the problem so I can specify this problem and solve?
I have tried with 'quadprog', as we can always rewrite a least squares problem as a quadratic optimization , and I think quadprog accepts sparse equality constraints. But there might be trouble if the matrix H of quadprog equivalent to A'*A of the lsqlin formulation is singular.
Any and all replies are really appreciated!
~Keshav
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