Nothing
llgpout <- function( tab, coefficients, targets )
{
###
### This function returns a list of named components with the decision variables,
### positive deviation variables and negative deviation variables.
###
### Parameters
### tab = a list of named components that specifies the modified simplex tableau
### coefficients = a matrix of the coefficients for the linear objective functions
### targets = a vector of the target values for the objective functions
###
### create vectors with the labels for the variables
###
x.headings <- paste( "X", 1:tab$variables, sep="" )
neg.headings <- paste( "N", 1:tab$objectives, sep="" )
pos.headings <- paste( "P", 1:tab$objectives,sep="" )
###
### allocate arrays for the output variables
###
x <- rep( 0, tab$variables )
n <- rep( 0, tab$objectives )
p <- rep( 0, tab$objectives )
###
### loop over the basic variables in the tableau
###
for ( i in 1:tab$objectives ) {
###
### loop over the decision variable labels
###
for ( j in 1:tab$variables ) {
if ( tab$row.headings[i] == x.headings[j] ) {
x[j] <- tab$tb[i]
}
}
###
### loop over the negative deviation variable labels
###
for ( j in 1:tab$objectives ) {
if ( tab$row.headings[i] == neg.headings[j] ) {
n[j] <- tab$tb[i]
}
}
###
### loop over the positive deviation variable labels
###
for ( j in 1: tab$objectives ) {
if ( tab$row.headings[i] == pos.headings[j] ) {
p[j] <- tab$tb[i]
}
}
}
f <- coefficients %*% x
output <- list( x=x, n=n, p=p, f=f, a=tab$ta, b=targets )
###
### define the llgpout class
###
class( output ) <- "llgpout"
return( output )
}
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