lapjv | R Documentation |
Find the matching of rows to columns that minimizes or maximizes the cost. See do_lap for usage.
lapjv(cost, maximize = FALSE)
lapmod(cost, maximize = FALSE)
cost |
For lapjv, an object that can be coerced to a matrix. For lapmod, a sparseMatrix. |
maximize |
If FALSE (default) then costs are minimized and if TRUE the costs are maximized |
The C++ code for these method is modified from code in the python lapjv package.
The cost matrix is padded with a single row and column of very large entries that helps to avoid stability issues with the algorithms.
The assignment of rows to columns as a vector.
R. Jonker, A. Volgenant (1987). A shortest augmenting path algorithm for dense and sparse linear assignment problems. Computing, pages 325-340.
A. Volgenant (1996). Linear and Semi-Assignment Problems: A Core Oriented Approach. Computer Ops Res., pages 917-932.
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