| lp.assign {lpSolve} | R Documentation |
Interface to lp_solve linear/integer programming system specifically for solving assignment problems
lp.assign (cost.mat, presolve=0, compute.sens=0)
cost.mat |
Matrix of costs: the ij-th element is the cost of assigning source i to destination j. |
presolve |
Numeric: presolve? Default 0 (no); any non-zero value means "yes." Currently ignored. |
compute.sens |
Numeric: compute sensitivity? Default 0 (no); any non-zero value means "yes." |
This is a particular integer programming problem. All the decision variables are assumed to be integers; each row has the constraint that its entries must add up to 1 (so that there is one 1 and the remaining entries are 0) and each column has the same constraint. This is assumed to be a minimization problem.
An lp object. See documentation for details.
Sam Buttrey, buttrey@nps.navy.mil
assign.costs <- matrix (c(2, 7, 7, 2, 7, 7, 3, 2, 7, 2, 8, 10, 1, 9, 8, 2), 4, 4)
## Not run:
> assign.costs
[,1] [,2] [,3] [,4]
[1,] 2 7 7 1
[2,] 7 7 2 9
[3,] 7 3 8 8
[4,] 2 2 10 2
## End(Not run)
lp.assign (assign.costs)
## Not run: Success: the objective function is 8
lp.assign (assign.costs)$solution
## Not run:
[,1] [,2] [,3] [,4]
[1,] 0 0 0 1
[2,] 0 0 1 0
[3,] 0 1 0 0
[4,] 1 0 0 0
## End(Not run)