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 ...