I have an optimization problem on a set of data that is solvable with the Hungarian Algorithm and works well on small sets. But the full set of data is large and only 0.1% of the cost matrix is even used (the rest of the values are invalid and maxInt is used in their place) it becomes computationally infeasible. I presume there may be a better way to handle things in this case and would like a pointer to any more specialized algorithms for this type of case.
Simplify the Hungarian Algorithm for cases of an extremely sparse cost matrix?
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combinatorics
optimization