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\name{readMps}
\alias{readMps}
\title{Read MPS Files}
\description{
This function reads MPS files - the standard format for Linear Programming problems.
}
\usage{
readMps( file, solve=FALSE, maximum=FALSE )
}
\arguments{
\item{file}{a character string naming the file to read.}
\item{solve}{logical. Should the problem be solved after reading it
from the file (using \code{\link{solveLP}})?}
\item{maximum}{logical. Should we maximize or minimize (the default)?}
}
\details{
Equality constraints and 'greater than'-bounds are not implemented yet.
}
\value{
\code{readMps} returns a list containing following objects:
\item{name}{the name of the Linear Programming problem.}
\item{cvec}{vector \eqn{c}.}
\item{bvec}{vector \eqn{b}.}
\item{Amat}{matrix \eqn{A}.}
\item{res}{if \code{solve} is TRUE, it contains the results of the solving
process (an object of class \code{\link{solveLP}}).}
}
\author{
Arne Henningsen
}
\seealso{
\code{\link{solveLP}}, \code{\link{writeMps}}
}
\examples{
## 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 ) )
## Write to MPS file
writeMps( "steinh.mps", cvec, bvec, Amat, "Steinhauser" )
## delete all LP objects
rm( cvec, bvec, Amat )
## Read LP data from MPS file and solve it.
lp <- readMps( "steinh.mps", TRUE, TRUE )
## Print the results
lp$res
## remove the MPS file
file.remove( "steinh.mps" )
}
\keyword{ optimize }
|
