Hello,

I need to solve a large scale MILP with a sparse constraint matrix using CPLEX within C++.

In my initial implementation, I do not exploit the sparsity of the constraint matrix, and feed all zero and non-zero elements of the constraint matrix to CPLEX. However, the problem is so large that it cannot even be load in memory.

So my question is: If I filter out the zero elements, and only feed the nonzero elements of the constraint matrix to CPLEX, will that help with memory issue?

If this helps, please share any advice/insight that you may have on the implementation side since this is a large problem with different classes of variables. I was running out of English alphabets when I was writing the formulation :)

Thanks

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Amin

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#DecisionOptimization