Louis Wasserman schrieb:
Yo,
Man, I'd never used FFI before, but it's really not as scary as I'd
feared.
I've implemented a more comprehensive interface to GLPK's simplex
solver and -- rather importantly, for my own needs -- its MIP solver.
This doesn't depend on hmatrix, and in fact, it doesn't require any
matrix or vector manipulation at all -- linear functions are specified
as a straight-up Data.Map from an arbitrary variable type to their
coefficients.
The library is now available as glpk-hs on hackage.
Example:
import Data.LinearProgram.LPMonad
import Data.LinearProgram
import Data.LinearProgram.GLPK
objFun :: LinFunc String Int
objFun = linCombination [(10, "x1"), (6, "x2"), (4, "x3")]
lp :: LP String Int
lp = execLPM $ do setDirection Max
setObjective objFun
leqTo (varSum ["x1", "x2", "x3"]) 100
leqTo (10 *^ var "x1" ^+^ 4 *& "x2" ^+^ 5 *^ var "x3") 600
-- c *^ var v, c *& v, and linCombination [(c, v)] are all equivalent.
-- ^+^ is the addition operation on linear functions.
leqTo (linCombination [(2, "x1"), (2, "x2"), (6, "x3")]) 300
varGeq "x1" 0
varBds "x2" 0 50
varGeq "x3" 0
setVarKind "x1" IntVar
setVarKind "x2" ContVar
Using strings for variable names you cannot check for undefined
variables. How about adding a function for generating new variables to
your LP monad?
The example may then look like
do
setDirection Max
setObjective objFun
x1 <- newVariable
x2 <- newVariable
x3 <- newVariable
leqTo (varSum [x1,x2,x3]) 100
...
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