Hi:
I am trying to implement a bandwidth reduction algorithm for a (M x
N) binary matrix using the GA package in R.
I am using the folloging code to get the optimal permutation for rows
and columns (optimization in two dimensions).
M <- matrix(c(0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0,
1),nrow=5, ncol=4)
BW <- function(patt, origMatrix) {
M1 <- origMatrix[patt[1], patt[2]]
temp2 <- 0;
temp3 <- 0;
for(i in 1:nrow(M1))
{
for(j in 1:ncol(M1))
{
if(M1[i,j] > 0)
{
temp1 <- abs(i - j)
temp2 <- append(temp2, temp1)
}
}
temp3 <- append(temp3, max(temp2))
temp2 <- 0
}
return(max(temp3))
}
bwFit <- function(patt, ...) 1/BW(patt[1], patt[2],...)
GA <- ga(type = "permutation", fitness = bwFit, origMatrix = M, min =
c(1,1), max = c(5,4), popSize = 100, maxiter = 5000, run = 500,
pmutation = 0.2)
I get this error message: Error in BW(patt[1], patt[2], ...) : unused
argument (patt[2])
In summary, I am unable to implement the optimization in two
dimensions. In the solution, I need two vectors containing the optimal row
and column permutations. Can you suggest a solution?
Regards:
John
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