Note that eliminating nodes that are not used typically have no effect on the solution time and memory requirements of the mathematical program due to the ability of the pre-processor to quickly reduce the matrix.
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On Mar 31, 2016, at 9:19 AM, Abhishek Shivakumar <address@hidden
I have an lp model that produces an extremely sparse constraint matrix. I would like to reduce the number of non-zero entries in this matrix (make the matrix more dense). The main cause of this sparse-ness is the relation between two parameters.
They can be seen as ‘arcs’ and ‘nodes: not all nodes have arcs between them. Is there a way to create a subset of parameter data from the sets ‘arcs’ and ‘nodes’ based on whether they are connected? I would then be able to apply constraints only for this subset.
In other languages (such as python) such an operation is possible through nested conditional statements. Is there a similar/equivalent approach in glpk/GNU mathprog?
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