Why does the conventional QP solver quadprog of MATLAB using the interior-point algorithm not fully exploit the sparse structure of matrices?
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It seems that the quadprog function of MATLAB, the (conventional) interior-point algorithm, is not fully exploiting the sparsity and structure of the sparse QP formulation based on my results.
In Model Predictive Control, the computational complexity should scale linearly with the prediction horizon N. However, results show that the complexity scales quadratically with the prediction horizon N.
What can be possible explanations?