Hello and thanks in advance. Fresh off the heels of this question I acquired some more RAM and now have enough memory to fit all the matrices I need to run a linear programming solver. Now the problem is none of the Linear Programming packages in R seem to support long vectors (ie large matrices).
I've tried functions Rsymphony_solve_LP
, Rglpk_solve_LP
and lp
from packages Rsymphony
, Rglpk
, and lpSolve
respectively. All report a similar error to the one below:
Error in rbind(const.mat, const.dir.num, const.rhs) :
long vectors not supported yet: bind.c:1544
I also have my code below in case that helps...the constraint matrix mat
is my big matrix (7062 rows by 364520 columns) created using the package bigmemory
. When I run this this line the matrix is pulled into memory and then after a while the errors show.
Rsymph <- Rsymphony_solve_LP(obj,mat[1:nrow(mat),1:ncol(mat)],dir,rhs,types=types,max=max, write_lp=T)
I'm guessing this is a hard-coded error in each of the three functions? Is there currently a linear programming solver in R or even Python that supports long vectors? Should I contact the package maintainers or just edit the code myself? Thanks!
The package lpSolveAPI
can solve long-vector linear programming problems. You have to first start my declaring a Linear Programming object, then add the constraints:
library(lpSolveAPI)
#Generate Linear Programming Object
lprec <- make.lp(nrow = 0 # Number of Constraints
, ncol = ncol(mat) # Number of Decision Variables
)
#Set Objective Function to Minimize
set.objfn(lprec, obj)
#Add Constraints
#Note Direction and RHS is included along with Constraint Value
for(i in 1:nrow(mat) ){
add.constraint(lprec,mat[i,], dir[i], rhs[i])
print(i)
}
#Set Decision Variable Type
set.type(lprec, c(1:ncol(mat)), type = c("binary"))
#Solve Model
solve(lprec)
#Obtain Solutions
get.total.iter(lprec)
get.objective(lprec)
get.variables(lprec)
There's a good introduction to this package here.