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library( linprog )
## example of Steinhauser, Langbehn and Peters (1992)
## Production activities
cvec <- c(1800, 600, 600) # gross margins
names(cvec) <- c("Cows","Bulls","Pigs")
## Constraints (quasi-fix factors)
bvec <- c(40, 90, 2500) # endowment
names(bvec) <- c("Land","Stable","Labor")
## Needs of Production activities
Amat <- rbind( c( 0.7, 0.35, 0 ),
c( 1.5, 1, 3 ),
c( 50, 12.5, 20 ) )
## solve the model
result1a <- solveLP( cvec, bvec, Amat, TRUE )
## Write to a (virtual) MPS file
mpsFile <- file()
writeMps( mpsFile, cvec, bvec, Amat, "Steinhauser" )
## write the lines of this file to the output file
mpsLines <- readLines( mpsFile )
close( mpsFile )
print( mpsLines )
## Write to a (virtual) MPS file again (for readMps)
mpsFile <- file()
writeMps( mpsFile, cvec, bvec, Amat, "Steinhauser" )
## delete all LP objects
rm( cvec, bvec, Amat )
## Read LP data from MPS file and solve it.
lpModel <- readMps( mpsFile, TRUE, TRUE )
close( mpsFile )
## Print the model and its result
lpModel
all.equal( result1a, lpModel$res )
## example 1.1.3 of Witte, Deppe and Born (1975)
## Two types of Feed
cvec <- c(2.5, 2 ) # prices of feed
names(cvec) <- c("Feed1","Feed2")
## Constraints (minimum (<0) and maximum (>0) contents)
bvec <- c(-10, -1.5, 12)
names(bvec) <- c("Protein","Fat","Fibre")
## Matrix A
Amat <- rbind( c( -1.6, -2.4 ),
c( -0.5, -0.2 ),
c( 2.0, 2.0 ) )
## solve the model
result2a <- solveLP( cvec, bvec, Amat )
## Write to a (virtual) MPS file
mpsFile <- file()
writeMps( mpsFile, cvec, bvec, Amat, "Steinhauser" )
## write the lines of this file to the output file
mpsLines <- readLines( mpsFile )
close( mpsFile )
print( mpsLines )
## Write to a (virtual) MPS file again (for readMps)
mpsFile <- file()
writeMps( mpsFile, cvec, bvec, Amat, "Steinhauser" )
## delete all LP objects
rm( cvec, bvec, Amat )
## Read LP data from MPS file and solve it.
lpModel <- readMps( mpsFile, TRUE )
close( mpsFile )
## Print the model and its result
lpModel
all.equal( result2a, lpModel$res )
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