TDA's gqap: given a flow graph and a distance graph (both
undirected, integer-valued), search for the assignment minimizing
total cost, with the GRASP heuristic of CACM algorithm 754.
Usage
tda_gqap(flow, dist, max_iterations = 100, ...)
Arguments
- flow, dist
symmetric integer matrices of equal dimension.
- max_iterations
iteration cap.
- ...
passed to tda_run.
Value
with direct exports enabled, a list with cost,
assignment and output; otherwise the printed
output lines.
Examples
f <- rbind(c(0, 3, 1), c(3, 0, 2), c(1, 2, 0))
d <- rbind(c(0, 1, 4), c(1, 0, 2), c(4, 2, 0))
tda_gqap(f, d)
#> <tda_assignment>
#> cost: 22
#> assignment: 1 2 3
#> permuted: 9 x 6 table
#> (full TDA output in $output, 58 lines)