diff --git a/CombinatorialOptimisation/SAT.hi b/CombinatorialOptimisation/SAT.hi new file mode 100644 Binary files /dev/null and b/CombinatorialOptimisation/SAT.hi differ diff --git a/CombinatorialOptimisation/SAT.hs b/CombinatorialOptimisation/SAT.hs --- a/CombinatorialOptimisation/SAT.hs +++ b/CombinatorialOptimisation/SAT.hs @@ -29,7 +29,7 @@ numUnSATEDClauses,getTrueFalseCount,summariseSAT,makeRandomSATProblem,flipVariable,satproblem,setAllVars,randomiseVariables )where -import qualified Data.Map as M +import qualified Data.IntMap as IM import qualified Data.Array as A import Data.List import System.Random @@ -41,8 +41,8 @@ numVariables :: Int, variableLookUp :: Int->([Int],[Int]), clauseLookUp :: Int->([Int],[Int]), - variablePosition :: M.Map Int Bool, - clausePosition :: M.Map Int Int} + variablePosition :: IM.IntMap Bool, + clausePosition :: IM.IntMap Int} instance Eq SATProblem where (==) s1 s2 = (numSATEDClauses s1) == (numSATEDClauses s2) && (variablePosition s1) == (variablePosition s2) @@ -57,7 +57,7 @@ it returns the number of variables in the True, and False positions. -} getTrueFalseCount :: SATProblem->(Int,Int) -getTrueFalseCount s = let ls = M.elems $ variablePosition s +getTrueFalseCount s = let ls = IM.elems $ variablePosition s in (length (filter (==True) ls),length (filter (==False) ls)) {- | The number of unsatisfied clauses in the problem, the inverse of @numSATEDClauses@ -} @@ -90,7 +90,7 @@ {- | Partial display function, for usage in show, displays the setting of each variable. -} showVARPosition :: SATProblem->String -showVARPosition s = concat [concat [" x",show v," = ",show t,"\n" ] |(v,t)<- M.assocs (variablePosition s)] +showVARPosition s = concat [concat [" x",show v," = ",show t,"\n" ] |(v,t)<- IM.assocs (variablePosition s)] {- | Alternative constructor for the data structure. Takes only those elements that can not be derived and correctly initialises the other components, such as calculating @@ -101,17 +101,17 @@ is present), the lookup table for clauses (clause index to lists of variable indexes) and the current settings of each variable. -} -satproblem :: Int->Int->(Int->([Int],[Int]))->(Int->([Int],[Int]))->M.Map Int Bool->SATProblem +satproblem :: Int->Int->(Int->([Int],[Int]))->(Int->([Int],[Int]))->IM.IntMap Bool->SATProblem satproblem nClauses nVars varLookup claLookup varPosition = SATProblem nClauses satClause nVars varLookup claLookup varPosition finalClausePosition where varList = [0 .. nVars -1] - initialClausePositions = M.fromList $ zip [0 .. nClauses -1] $ repeat 0 - finalClausePosition = foldl f M.empty [0 .. nVars -1] + initialClausePositions = IM.fromList $ zip [0 .. nClauses -1] $ repeat 0 + finalClausePosition = foldl f IM.empty [0 .. nVars -1] f m v = let (ords,negs) = varLookup v - varPos = varPosition M.! v - in if varPos then foldl (\m' c->M.adjust (+1) c m') m ords else foldl (\m' c->M.adjust (+1) c m') m negs - satClause = sum $ map (\x->if x ==0 then 0 else 1) (M.elems finalClausePosition) + varPos = varPosition IM.! v + in if varPos then foldl (\m' c->IM.adjust (+1) c m') m ords else foldl (\m' c->IM.adjust (+1) c m') m negs + satClause = sum $ map (\x->if x ==0 then 0 else 1) (IM.elems finalClausePosition) {- | For rapid initialisation of problem instances. This fixes the setting of all variables to either true or false. The effect this has on the number @@ -120,7 +120,7 @@ setAllVars :: Bool->SATProblem->SATProblem setAllVars b s = satproblem (numClauses s) (numVariables s) (variableLookUp s) (clauseLookUp s) initialVarPosition where - initialVarPosition = M.fromList $ zip [0 .. numVariables s -1] $ repeat b + initialVarPosition = IM.fromList $ zip [0 .. numVariables s -1] $ repeat b {- | For rapid initialisation of problem instances for usage in stochastic algorithms. Specifically expected to be used for genetic algorithms and other forms of @@ -129,7 +129,7 @@ randomiseVariables :: RandomGen g=>g->SATProblem->SATProblem randomiseVariables g s = satproblem (numClauses s) (numVariables s) (variableLookUp s) (clauseLookUp s) varpos where - varpos = M.fromList $ zip [0 .. (numVariables s) -1] $ (randoms g :: [Bool]) + varpos = IM.fromList $ zip [0 .. (numVariables s) -1] $ (randoms g :: [Bool]) {- | I am not sure how often this will be used in practice, as randomly created problems often seem to be quite easy to solve. Requires a source of random numbers, the number @@ -140,7 +140,7 @@ makeRandomSATProblem gen numVariables numClauses = satproblem numClauses numVariables varLookup claLookup initialVarPosition where - initialVarPosition = M.fromList $ zip [0 .. numVariables -1] $ repeat False + initialVarPosition = IM.fromList $ zip [0 .. numVariables -1] $ repeat False clauses = take numClauses $ nub (unfoldr generateRandomClause gen) generateRandomClause g = let f (ms,ns) gen' | length ms + length ns == 3 = (ms,ns,gen') @@ -152,11 +152,11 @@ else f (ms,n:ns) gen''' (ords,negs,g') = f ([],[]) g in Just ((sort ords,sort negs),g') - emptyClauseData = M.fromList $ zip [0 .. numVariables -1] (repeat ([],[])) + emptyClauseData = IM.fromList $ zip [0 .. numVariables -1] (repeat ([],[])) basicClauseLookup = foldl constructClauseLookup emptyClauseData $ zip [0..] clauses - varLookup = ((A.listArray (0,numVariables-1) (M.elems basicClauseLookup)) A.!) - constructClauseLookup m (clauseIndex,(ords,negs)) = let addNeg m' x = M.adjust (\(as,bs)->(as,clauseIndex:bs)) x m' - addOrd m' x = M.adjust (\(as,bs)->(clauseIndex:as,bs)) x m' + varLookup = ((A.listArray (0,numVariables-1) (IM.elems basicClauseLookup)) A.!) + constructClauseLookup m (clauseIndex,(ords,negs)) = let addNeg m' x = IM.adjust (\(as,bs)->(as,clauseIndex:bs)) x m' + addOrd m' x = IM.adjust (\(as,bs)->(clauseIndex:as,bs)) x m' in foldl addNeg (foldl addOrd m ords) negs claLookup = ((A.listArray (0,numVariables-1) clauses) A.!) @@ -167,20 +167,20 @@ flipVariable :: Int->SATProblem->(SATProblem,Int) flipVariable v s - = let modifiedVarPos = M.insert v changedVar (variablePosition s) + = let modifiedVarPos = IM.insert v changedVar (variablePosition s) in (s{numSATEDClauses=numSATEDClauses s + overAllChange,variablePosition=modifiedVarPos,clausePosition=modifiedClausePos},overAllChange) where overAllChange = ordChange + negChange - changedVar = not $ (variablePosition s) M.! v + changedVar = not $ (variablePosition s) IM.! v (ords,negs) = (variableLookUp s) v cp = clausePosition s (cp',ordChange) = if changedVar then foldl countInc (cp,0) ords else foldl countDec (cp,0) ords (modifiedClausePos,negChange) = if changedVar then foldl countDec (cp',0) negs else foldl countInc (cp',0) negs - countInc (positions,counter) i = let current = positions M.! i + countInc (positions,counter) i = let current = positions IM.! i counter' = if current == 0 then counter+1 else counter - in (M.insert i (current+1) positions,counter') - countDec (positions,counter) i = let current = positions M.! i + in (IM.insert i (current+1) positions,counter') + countDec (positions,counter) i = let current = positions IM.! i counter' = if current == 1 then counter-1 else counter - in (M.insert i (current-1) positions,counter') + in (IM.insert i (current-1) positions,counter') diff --git a/CombinatorialOptimisation/SAT.o b/CombinatorialOptimisation/SAT.o new file mode 100644 Binary files /dev/null and b/CombinatorialOptimisation/SAT.o differ diff --git a/CombinatorialOptimisation/TSP.hi b/CombinatorialOptimisation/TSP.hi new file mode 100644 Binary files /dev/null and b/CombinatorialOptimisation/TSP.hi differ diff --git a/CombinatorialOptimisation/TSP.hs b/CombinatorialOptimisation/TSP.hs --- a/CombinatorialOptimisation/TSP.hs +++ b/CombinatorialOptimisation/TSP.hs @@ -42,12 +42,13 @@ ----------------------------------------------------------------------------- module CombinatorialOptimisation.TSP( - TSPProblem(TSPProblem,routeMap,numCities,routeElementToIndex,indexToRouteElement), - edgeCost,solutionValue,getTSPPathAsList, + TSPProblem(TSPProblem,numCities,cityNameToIndex,indexToCityName,solutionValueI,edgeCostI), + edgeCost,solutionValue,getTSPPathAsList,routeMap,generateDirectionalRouteMap, InternalStorage(ExplicitMatrix,TriangularMatrix,Recomputation), showEdgeWeights, - exchangeCities, - exchangeCitiesOnIndex, + swapCities, + swapCitiesOnIndex, + kFragments,allVariations,minimumVariation, stochasticReversal, shuffleFragments, evaluateRouteNaive, randomiseRoute, setRoute, @@ -57,6 +58,7 @@ )where import qualified Data.Map as M +import qualified Data.IntMap as IM import qualified Data.Array as A import System.Random import Data.List @@ -80,13 +82,40 @@ -} data TSPProblem = TSPProblem { solutionValueI :: FP, - routeMap :: M.Map Int (Int,Int), edgeCostI :: (Int->Int->FP), numCities :: Int, - routeElementToIndex :: M.Map Int Int, - indexToRouteElement :: M.Map Int Int + cityNameToIndex :: IM.IntMap Int, + indexToCityName :: IM.IntMap Int } +cityAtIndex :: TSPProblem->Int->Int +cityAtIndex t i | i>=numCities t = cityAtIndex t (i-numCities t) + | otherwise = indexToCityName t IM.! i + +{- | Will generate an IntMap of the path, giving city to next and last city names as the structure. + This is effectively the edges involved in the process. Wow, how badly written was that. -} +generateDirectionalRouteMap :: TSPProblem->IM.IntMap (Int,Int) +generateDirectionalRouteMap t | null path = IM.fromList [] + | length path == 1 = IM.fromList [(head path,(head path,head path))] + | otherwise = IM.fromList path' + where + path = IM.elems . routeMap $ t + end = last path + fr = (head path,(end,path !! 1)) + bk = (end,(last . init $ path,head path)) + path' = fr:[(b,(a,c)) | (a,b,c)<-zip3 path (tail path) (tail $ tail path)]++[bk] + +{- | The definition of equality is quite slow, it will check the internal representation of the path that +the solution follows. -} +instance Eq TSPProblem where + a == b = cityNameToIndex a == cityNameToIndex b + +{- | The definition of orderability is much faster, coming down to a simple integer comparison.-} +instance Ord TSPProblem where + compare a b = compare (solutionValueI a) (solutionValueI b) + +routeMap = indexToCityName + {- | Internally the value of the solution is stored as a fixed point value, stored in an Int64 data type. For external visibility however this function is provided, converting the value into a floating point numbers. -} @@ -113,13 +142,12 @@ instance Show TSPProblem where show t = concat ["TSPProblem of ",show . numCities $ t, - " cities\n Current Solution ",show . getTSPPathAsList $ t, + " cities\n Current Solution ",show . getTSPPathAsList 0 $ t, "\n Costing ",show . solutionValue $ t,"\n"] -getTSPPathAsList :: TSPProblem->[Int] -getTSPPathAsList t = let rm = snd . ((M.!) (routeMap t)) - in 0:(takeWhile (\x->x/=0) $ iterate rm (rm 0))++[0] - +getTSPPathAsList :: Int->TSPProblem->[Int] +getTSPPathAsList alignOn t = let (as,bs) = span (/=alignOn) . IM.elems . routeMap $ t in bs++as + {- | Converts the lookup table of a problem into a comma and newline delimited string. This should facilitate copying into spreadsheets for checking the problem being used and validating solutions by hand. -} @@ -136,11 +164,11 @@ in the path. It looks up the current indexes by city name and passes the work off to @exchangeCitiesOnIndex@. -} -exchangeCities :: Int->Int->TSPProblem->TSPProblem -exchangeCities a b t = exchangeCitiesOnIndex i1 i2 t +swapCities :: Int->Int->TSPProblem->TSPProblem +swapCities a b t = swapCitiesOnIndex i1 i2 t where - i1 = routeElementToIndex t M.! a - i2 = routeElementToIndex t M.! b + i1 = cityNameToIndex t IM.! a + i2 = cityNameToIndex t IM.! b {- | Performs the bulk of the work for exchanging elements of the cycle. This version no longer assumes the indices are ordered due to confusion this @@ -148,52 +176,56 @@ 0 and last. This is now fixed. -} -exchangeCitiesOnIndex :: Int->Int->TSPProblem->TSPProblem -exchangeCitiesOnIndex i1 i2 t - | i1 > i2 = exchangeCitiesOnIndex i2 i1 t +swapCitiesOnIndex :: Int->Int->TSPProblem->TSPProblem +swapCitiesOnIndex i1 i2 t + | i1 > i2 = swapCitiesOnIndex i2 i1 t | d == 0 = t - | d == 1 = t{routeMap=rAdj,solutionValueI=solutionValueI t + priceChangeAdj,routeElementToIndex=t2',indexToRouteElement=t1'} - | d == (numCities t -1) = t{routeMap=rAdj',solutionValueI=solutionValueI t + priceChangeAdj',routeElementToIndex=t2',indexToRouteElement=t1'} - | otherwise = t{routeMap=r',solutionValueI=solutionValueI t + priceChange,routeElementToIndex=t2',indexToRouteElement=t1'} + | d == nc = t{solutionValueI=solutionValueI t + priceChangeAdjC, + cityNameToIndex=cnti, + indexToCityName = itcn} -- adjacent wrap around + | d == 1 = t{solutionValueI=solutionValueI t + priceChangeAdjA, + cityNameToIndex=cnti, + indexToCityName = itcn} -- adjacent indexes + | otherwise = t{solutionValueI=solutionValueI t + priceChangeAdjB, + cityNameToIndex=cnti, + indexToCityName = itcn} where - d = abs (i1 - i2) - - -- basic setup - r = (routeMap t) - a = indexToRouteElement t M.! i1 - b = indexToRouteElement t M.! i2 + d = i2 - i1 + + -- basic setup (common code) + t1 = indexToCityName t + a = t1 IM.! i1 + b = t1 IM.! i2 p = edgeCostI t - ((a1,a2),(b1,b2)) = (r M.! a,r M.! b) + nc = numCities t -1 - -- usual code - priceChange = sum [p a1 b,p b a2,p b1 a,p a b2] - sum [p a a2,p b b2,p a1 a,p b1 b] - r' = foldl' (\m (k,f) -> M.adjust f k m) r [(a,\_->(b1,b2)),(b,\_->(a1,a2)),(a1,\(x,y)->(x,b)),(a2,\(x,y)->(b,y)),(b1,\(x,y)->(x,a)),(b2,\(x,y)->(a,y))] + -- index exchange (common code) + itcn = IM.insert i2 a (IM.insert i1 b t1) + cnti = IM.insert b i1 (IM.insert a i2 $ cityNameToIndex t) - -- index exchange - t1 = indexToRouteElement t - t2 = routeElementToIndex t - t2' = M.insert b i1 (M.insert a i2 t2) - t1' = M.insert i1 b (M.insert i2 a t1) - - -- adjacent exchange, special case - -- failed code => priceChangeAdj = sum [p a1 b,p b a,p a b2] - sum[p a1 a,p a b,p b b2] - priceChangeAdj = sum $ zipWith (-) [p a1 b,p b a,p a b2] [p a1 a,p a b,p b b2] - rAdj = foldl' (\m (k,f) -> M.adjust f k m) r [(a1,\(x,y)->(x,b)),(b2,\(x,y)->(a,y)),(a,\_->(b,b2)),(b,\_->(a1,a))] - -- special adjacent, first and last - priceChangeAdj' = sum $ zipWith (-) [p b1 a,p a b,p b a2] [p b1 b,p b a,p a a2] - rAdj' = foldl' (\m (k,f) -> M.adjust f k m) r [(a2,\(x,y)->(b,y)),(b1,\(x,y)->(x,a)),(a,\_->(b1,b)),(b,\_->(a,a2))] + -- find related cities + a1 = if i1 == 0 then t1 IM.! nc else t1 IM.! (i1 -1) + a2 = t1 IM.! (i1 +1) + b1 = t1 IM.! (i2 -1) + b2 = if i2 == nc then t1 IM.! 0 else t1 IM.! (i2 +1) + -- pricing codes + priceChangeAdjB = sum [p a1 b,p b a2,p b1 a,p a b2] - sum [p a a2,p b b2,p a1 a,p b1 b] + priceChangeAdjA = sum [p a1 b,p b a,p a b2] - sum [p a1 a,p a b,p b b2] + priceChangeAdjC = sum [p b1 a,p a b,p b a2] - sum [p b1 b,p b a,p a a2] + {- | A brute force recalculation of the current length of the path. Use sparingly.-} evaluateRouteNaive :: TSPProblem->TSPProblem -evaluateRouteNaive t = t{solutionValueI=evalRoute 0} +evaluateRouteNaive t = t{solutionValueI=sum' 0 rm (tail $ cycle rm)} + -- . zipWith ep rm $ (tail $ cycle rm)} -- evalRoute rm} where ep = edgeCostI t - rm = snd . ((M.!) (routeMap t)) - evalRoute x = let n = rm x - in if n==0 then ep x n - else ep x n + evalRoute n - + rm = IM.elems (routeMap t) + sum' v [x] (y:_) = v+ep x y + sum' v (x:xs) (y:ys) = let n = ep x y + v in n `seq` sum' n xs ys + + {- | Take a path through the system and a problem, insert the path into the system, calculating distances and setting up appropriate look up tables. It does not validate the list in terms of going through all the cities, or going through @@ -201,20 +233,64 @@ very very fast). It does organise the list so that the starting node is vertex 0. Uses the @evaluateRouteNaive@ to calculate the length of the path via a brute - force method. This is not expected to be used frequently. -} + force method. This is not expected to be used frequently. -} setRoute :: [Int]->TSPProblem->TSPProblem -setRoute path t = evaluateRouteNaive t{routeMap=newRoute,indexToRouteElement=in1,routeElementToIndex=in2} +setRoute path t = evaluateRouteNaive t{indexToCityName=in1,cityNameToIndex=in2} where - l = dropWhile (/=0) $ cycle path - l' = tail l - l'' = tail l' - (k,k':_) = span (\(_,x,_)->x/=0) $ zip3 l l' l'' - newRoute = foldl' (\m (a,b,c) -> M.insert b (a,c) m) M.empty (k':k) - in1 = M.fromList $ zip [0..] (take (numCities t) l) - in2 = M.fromList . (map swap) . M.assocs $ in1 - swap (a,b) = (b,a) + in1 = IM.fromList $ zip [0..] path + in2 = IM.fromList $ zip path [0..] +{- | An implementation of kexchange methods as a series of combinators. kFragments + will break a problem at specified edges and give back the path segments. + allVariations will take a set of segments and give back every possible combination of them, + and their reversals (I feel this should be broken down further, due to similarities with the + stochastic segment reversal method). allVariations is also a more general function than + the others, not actually requiring reference to TSP. + minimumVariation is expected to be used with a set of paths (probably generated by the above two methods) + and give only the best. + + stochasticReversal and shuffleFragments are similarly not really approapriate just here, but for now they + stay. Together they allow for less detailed k-exchange methods, for example, rather than exhaustively creating + variations, we will use it as a mutator for a GA. For this we might want to only create 1 permutation, which + can be done as; kFragments >>> shuffleFragments >>> stochasticReversal >>> \as->[concat as] >>> minimumVariation + + kFragments will begin by being quite fragile. Please make sure that your input sequence is + assending and does not include duplicates. Remember to initialise your route before calling this. -} + +kFragments :: [Int]->TSPProblem->[[Int]] +kFragments (first:xs) t = (\(a,b)->a:b) $ foldl f (basePath,[]) xs + where + basePath = getTSPPathAsList (cityAtIndex t (first +1)) t + f (b,col) x = let c = cityAtIndex t (x+1) + in (dropWhile (/=c) b,takeWhile (/=c) b:col) + +allVariations :: Bool->[[Int]]->[[Int]] +allVariations reversalAllowed fragments + | reversalAllowed = rebuildR fragments [] + | otherwise = rebuild fragments [] + where + -- rebuildR :: [[Int]]->[Int]->[TSPProblem] + rebuild [] xs = [xs] + rebuild (x:xs) [] = rebuild xs x + rebuild xs cp = concat [ rebuild ys (x++cp) | (x,ys)<-dropEach xs] + rebuildR [] xs = [xs] + rebuildR (x:xs) [] = rebuildR xs x ++ rebuildR xs (reverse x) + rebuildR xs cp = concat [ rebuildR ys (x++cp) ++ rebuildR ys (reverse x ++cp) | (x,ys)<-dropEach xs] + dropEach xs = f ([],xs) + where + f (as,b:[]) = (b,reverse as):[] + f (as,b:bs) = (b,reverse as ++ bs) : f (b:as,bs) + +minimumVariation :: TSPProblem->[[Int]]->TSPProblem +minimumVariation t = minimum . map (flip setRoute t) + +shuffleFragments :: Ord a=>[a]->[[Int]]->[[Int]] +shuffleFragments as = map snd . sortBy (\a b->compare (fst a) (fst b)) . zip as + +stochasticReversal :: [Bool]->[[Int]]->[[Int]] +stochasticReversal as = zipWith (\a b->if a then reverse b else b) as + {- | Shuffles a simple list of cities and then passes off the work to setRoute. -} randomiseRoute :: RandomGen g=>g->TSPProblem->TSPProblem @@ -234,7 +310,7 @@ matrix = M.fromList $ zip cityCoords (map realToFrac $ randomRs distanceLimits g) -- p' = (\x y->M.findWithDefault 0 (x,y) matrix) explicit = A.listArray (0,numCities*numCities-1) [M.findWithDefault 0 (a,b) matrix | a<-cities,b<-cities] - in TSPProblem 0 M.empty (\x y->explicit A.! (y * numCities + x)) numCities M.empty M.empty + in TSPProblem 0 (\x y->explicit A.! (y * numCities + x)) numCities IM.empty IM.empty -- TSPProblem 0 M.empty p numCities M.empty M.empty {- | Construct a TSPProblem instance for a Symmetric TSP. That is, the distance @@ -256,7 +332,7 @@ triangular = A.listArray (0,sum [0..numCities]) [M.findWithDefault 0 (a,b) matrix | a<-cities,b<-[0..a]] p = if storageType == ExplicitMatrix then (\x y->explicit A.! (y * numCities + x)) else (\x y->let x' = min x y; y' = max x y in triangular A.! (div (y'*y'+y') 2 + x')) - in TSPProblem 0 M.empty p numCities M.empty M.empty + in TSPProblem 0 p numCities IM.empty IM.empty {- | Construct a TSPProblem instance for a Symmetric TSP. The route will not be initially set up, the dictionaries will be empty. This does create the @@ -278,7 +354,7 @@ ExplicitMatrix -> \x y->explicit A.! (y * numCities + x) TriangularMatrix -> (\x y->let x' = min x y; y' = max x y in triangular A.! (div (y'*y'+y') 2 + x')) Recomputation -> \a b->if a == b then 0 else euclidianDistance (posArr A.! a) (posArr A.! b) - in TSPProblem 0 M.empty p numCities M.empty M.empty + in TSPProblem 0 p numCities IM.empty IM.empty where euclidianDistance :: (Double,Double)->(Double,Double)->FP euclidianDistance (a,b) (c,d) = realToFrac $ sqrt ((a-c)*(a-c)+(b-d)*(b-d)) diff --git a/CombinatorialOptimisation/TSP.o b/CombinatorialOptimisation/TSP.o new file mode 100644 Binary files /dev/null and b/CombinatorialOptimisation/TSP.o differ diff --git a/CombinatorialOptimisation/TSP/FixedPoint.hi b/CombinatorialOptimisation/TSP/FixedPoint.hi new file mode 100644 Binary files /dev/null and b/CombinatorialOptimisation/TSP/FixedPoint.hi differ diff --git a/CombinatorialOptimisation/TSP/FixedPoint.hs b/CombinatorialOptimisation/TSP/FixedPoint.hs --- a/CombinatorialOptimisation/TSP/FixedPoint.hs +++ b/CombinatorialOptimisation/TSP/FixedPoint.hs @@ -21,17 +21,21 @@ -- shifting, probably not that fast. ----------------------------------------------------------------------------- -module CombinatorialOptimisation.TSP.FixedPoint (FP(FP)) where +module CombinatorialOptimisation.TSP.FixedPoint (FP(FP),unwrappedFP,doubleToFP,fpToDouble) where import Data.Int import Data.Bits import Data.Ratio +import Foreign.C.Types + -- simple fixed point library, using 64 bit integers as the basis and 32 bits below the point (leaves 31 above, these are still signed) fixedPoint = 32 divConstI = 2^fromIntegral fixedPoint divConstD = 2**fromIntegral fixedPoint +divConstC :: CDouble +divConstC = fromIntegral divConstI fpOne = fromInteger 1 newtype FP = FP Int64 deriving (Eq,Ord) @@ -51,14 +55,23 @@ instance Fractional FP where (/) (FP a) (FP b) = FP $ fromInteger (div (shiftL (toInteger a) fixedPoint) (toInteger b)) recip = (/) fpOne - fromRational x = doubleToFP $ fromRational x + fromRational = doubleToFP . fromRational instance Real FP where toRational (FP a) = (fromIntegral a) % divConstI + + +fpToDouble :: FP->Double +fpToDouble (FP x) = realToFrac (fromIntegral x / divConstC) + doubleToFP :: Double->FP -doubleToFP x = let (a,b) = properFraction x - in fromInteger a + FP (floor (b * divConstD)) +doubleToFP = FP . unwrappedFP + +unwrappedFP :: Double->Int64 +unwrappedFP x = let (a,b) = properFraction x + in (shiftL (fromInteger a) fixedPoint) + (floor (b * divConstD)) + five,six :: FP five = fromInteger 5 diff --git a/CombinatorialOptimisation/TSP/FixedPoint.o b/CombinatorialOptimisation/TSP/FixedPoint.o new file mode 100644 Binary files /dev/null and b/CombinatorialOptimisation/TSP/FixedPoint.o differ diff --git a/CombinatorialOptimisation/TSP/TestFixedPoint.hs b/CombinatorialOptimisation/TSP/TestFixedPoint.hs new file mode 100644 --- /dev/null +++ b/CombinatorialOptimisation/TSP/TestFixedPoint.hs @@ -0,0 +1,44 @@ +-- don't know how to use small check at this point, going to go with an error based approach. + +import FixedPoint +import System.Random + +main :: IO() +main = do gen1<-newStdGen + let testGroup1 = makeTestGroup 500 gen1 + gen2<-newStdGen + let testGroup2 = makeTestGroup 500 gen2 + print "SUMMATIONS" + print $ ("Floats",sum testGroup1) + print $ ("Doubles",sum .con' $ testGroup1) + print $ ("FPs",sum . con $ testGroup1) + putStrLn "" + print "RECIPROCALS" + print $ ("Floats",sum $ map recip testGroup1) + print $ ("Doubles",sum $ map recip $ con' testGroup1) + print $ ("FPs",sum $ map recip $ con testGroup1) + putStrLn "" + print "SUM DIFF" + print $ ("Floats",sum $ zipWith (-) testGroup1 testGroup2) + print $ ("Doubles",sum $ zipWith (-) (con' testGroup1) (con' testGroup2)) + print $ ("FPs",sum $ zipWith (-) (con testGroup1) (con testGroup2)) + putStrLn "" + print "SUM DIV" + print $ ("Floats",sum $ zipWith (/) testGroup1 testGroup2) + print $ ("Doubles",sum $ zipWith (/) (con' testGroup1) (con' testGroup2)) + print $ ("FPs",sum $ zipWith (/) (con testGroup1) (con testGroup2)) + putStrLn "" + print "SUM MUL" + print $ ("Floats",sum $ zipWith (*) testGroup1 testGroup2) + print $ ("Doubles",sum $ zipWith (*) (con' testGroup1) (con' testGroup2)) + print $ ("FPs",sum $ zipWith (*) (con testGroup1) (con testGroup2)) + + +makeTestGroup :: RandomGen g=>Int->g->[Float] +makeTestGroup s g = take s $ randomRs (0,500) g + +con :: [Float]->[FP] +con = map realToFrac + +con' :: [Float]->[Double] +con' = map realToFrac diff --git a/FileFormat/SATLIB.hi b/FileFormat/SATLIB.hi new file mode 100644 Binary files /dev/null and b/FileFormat/SATLIB.hi differ diff --git a/FileFormat/SATLIB.hs b/FileFormat/SATLIB.hs --- a/FileFormat/SATLIB.hs +++ b/FileFormat/SATLIB.hs @@ -18,8 +18,9 @@ import CombinatorialOptimisation.SAT import Data.List -import qualified Data.Map as M +-- import qualified Data.Map as M import qualified Data.Array as A +import qualified Data.IntMap as IM {- | Loading routine that takes the file path and returns a SATProblem. All variables will be set to false in the initial setup, and the truth values of all clauses set appropriately. -} @@ -32,10 +33,10 @@ let (varCount,clauseCount) = if problemLine !! 1 /= "cnf" then error "This is not a CNF file" else (read $ problemLine !! 2,read $ problemLine !! 3) :: (Int,Int) let clauseLines = (map processClause) . (mySplit 0) . (map read) . (concatMap words) . tail $ ls - let clauseMap = foldl f (M.fromList (zip [0 .. varCount -1] $ repeat ([],[]))) (zip [0..] clauseLines) - let varLook = ((A.listArray (0,varCount -1) (M.elems clauseMap)) A.!) + let clauseMap = foldl f (IM.fromList (zip [0 .. varCount -1] $ repeat ([],[]))) (zip [0..] clauseLines) + let varLook = ((A.listArray (0,varCount -1) (IM.elems clauseMap)) A.!) let claLook = ((A.listArray (0,clauseCount -1) clauseLines) A.!) - return $ satproblem clauseCount varCount varLook claLook (M.fromList $ zip [0 .. varCount -1] $ repeat False) + return $ satproblem clauseCount varCount varLook claLook (IM.fromList $ zip [0 .. varCount -1] $ repeat False) where mySplit target xs = mySplit' [] xs where @@ -44,8 +45,8 @@ mySplit' ns (x:xs) | x == target = (reverse ns) : mySplit' [] xs | otherwise = mySplit' (x:ns) xs processClause cs = let (as,bs) = partition (>0) cs in (map ((+) (-1)) as,map ((+) (-1)) $ map abs bs) - f m (clauseIndex,(ords,negs)) = let addNeg m' x = M.adjust (\(as,bs)->(as,clauseIndex:bs)) x m' - addOrd m' x = M.adjust (\(as,bs)->(clauseIndex:as,bs)) x m' + f m (clauseIndex,(ords,negs)) = let addNeg m' x = IM.adjust (\(as,bs)->(as,clauseIndex:bs)) x m' + addOrd m' x = IM.adjust (\(as,bs)->(clauseIndex:as,bs)) x m' in foldl addNeg (foldl addOrd m ords) negs {- | Save routine for SATProblem, outputs back into SATLIB cnf format. The code @(loadCNFFile f) >>= (saveAsCNF f)@ should diff --git a/FileFormat/SATLIB.o b/FileFormat/SATLIB.o new file mode 100644 Binary files /dev/null and b/FileFormat/SATLIB.o differ diff --git a/FileFormat/TSPLIB.hi b/FileFormat/TSPLIB.hi new file mode 100644 Binary files /dev/null and b/FileFormat/TSPLIB.hi differ diff --git a/FileFormat/TSPLIB.hs b/FileFormat/TSPLIB.hs --- a/FileFormat/TSPLIB.hs +++ b/FileFormat/TSPLIB.hs @@ -29,7 +29,11 @@ import CombinatorialOptimisation.TSP import Data.Maybe import qualified Data.Map as M +import qualified Data.IntMap as IM import qualified Data.Array as A +import qualified Data.Array.Unboxed as U +import qualified Data.ByteString.Char8 as B +import qualified Data.ByteString.Lex.Double as BL import Data.List -- going to use a fixed point internal representation, only doing addition afterall @@ -39,27 +43,27 @@ {- | Simple 2d Euclidian. -} -euclidianDistance :: (Double,Double)->(Double,Double)->Double -euclidianDistance (a,b) (c,d) = sqrt ((a-c)*(a-c)+(b-d)*(b-d)) +euclidianDistance :: Double->Double->Double->Double->Double +euclidianDistance a b c d = sqrt ((a-c)*(a-c)+(b-d)*(b-d)) {- | Always rounded up Euclidian. -} -euclidianDistanceCeil :: (Double,Double)->(Double,Double)->Double -euclidianDistanceCeil a b = fromIntegral . ceiling $ euclidianDistance a b +euclidianDistanceCeil :: Double->Double->Double->Double->Double +euclidianDistanceCeil a b c d = fromIntegral . ceiling $ euclidianDistance a b c d {- | For only two types of file. Basically a form of rounded Euclidian. -} -pseudoEuclideanDistance :: (Double,Double)->(Double,Double)->Double -pseudoEuclideanDistance (a,b) (c,d) = let e = sqrt (((a-c)*(a-c)+(b-d)*(b-d)) /10 ) - f = fromIntegral (floor e) - in if fDouble->Double->Double->Double +pseudoEuclideanDistance a b c d = let e = sqrt (((a-c)*(a-c)+(b-d)*(b-d)) /10 ) + f = fromIntegral (floor e) + in if f(Double,Double)->Double -geoDistance (x1,y1) (x2,y2) = encodeFloat (floor dij) 0 +geoDistance :: Double->Double->Double->Double->Double +geoDistance x1 y1 x2 y2 = encodeFloat (floor dij) 0 where q1 = cos (lon1 - lon2) q2 = cos (lat1 - lat2) @@ -78,7 +82,14 @@ {- | A data type for representing bits of the specification section of a file. Assumed to be used later as a list of Specifications. -} -data Specification = IGNORE String | USEFUL String String | ENDSPEC String | FAIL String deriving Show +data Specification = IGNORE B.ByteString + | USEFUL SpecificationName B.ByteString + | ENDSPEC B.ByteString + | FAIL B.ByteString deriving Show +data SpecificationName = TYPE | DIMENSION | EDGEWEIGHTTYPE | EDGEWEIGHTFORMAT + | DATAPARTTYPE deriving (Show, Eq) +nodeCoordConst = B.pack "NODE COORD" +edgeWeightConst = B.pack "EDGE WEIGHT" {- | Test for filtering specification lines, so we only get data we might want to use. Could be got rid of as most of the time I do dictionary lookups on the output of the specification @@ -90,35 +101,36 @@ {- | Helper routine for @readSpecification@. Reads a single line (assumes that input is already line by line). -} -readSpecificationLine :: String->Specification +readSpecificationLine :: B.ByteString->Specification readSpecificationLine s - | likeString "NAME" s = IGNORE s - | likeString "TYPE" s = USEFUL "Type" (trim s) - | likeString "NODE_COORD_SECTION" s = ENDSPEC "NODE COORD" - | likeString "EDGE_WEIGHT_SECTION" s = ENDSPEC "EDGE WEIGHT" - | likeString "COMMENT" s = IGNORE s - | likeString "DIMENSION" s = USEFUL "Dimension" (trim s) - | likeString "DISPLAY_DATA_TYPE" s = IGNORE s - | likeString "EDGE_WEIGHT_TYPE" s = USEFUL "EdgeWeightType" (trim s) - | likeString "EDGE_WEIGHT_FORMAT" s = USEFUL "EdgeWeightFormat" (trim s) - | otherwise = FAIL $ "unrecognised field in specification : "++s + | likeString (B.pack "NAME") s = IGNORE s + | likeString (B.pack "TYPE") s = USEFUL TYPE (trim s) + | likeString (B.pack "NODE_COORD_SECTION") s = ENDSPEC nodeCoordConst + | likeString (B.pack "EDGE_WEIGHT_SECTION") s = ENDSPEC edgeWeightConst + | likeString (B.pack "COMMENT") s = IGNORE s + | likeString (B.pack "DIMENSION") s = USEFUL DIMENSION (trim s) + | likeString (B.pack "DISPLAY_DATA_TYPE") s = IGNORE s + | likeString (B.pack "EDGE_WEIGHT_TYPE") s = USEFUL EDGEWEIGHTTYPE (trim s) + | likeString (B.pack "EDGE_WEIGHT_FORMAT") s = USEFUL EDGEWEIGHTFORMAT (trim s) + | otherwise = FAIL $ B.append (B.pack "unrecognised field in specification : ") s where - likeString q s = take (length q) s == q - trim s = let s' = (dropWhile (==' ')) . (drop 1) . (dropWhile (/=':')) $ s - in reverse . (dropWhile (==' ')) . reverse $ s' + likeString q s = B.take (B.length q) s == q + trim s = let s' = (B.dropWhile (==' ')) . (B.drop 1) . (B.dropWhile (/=':')) $ s + in B.reverse . (B.dropWhile (==' ')) . B.reverse $ s' {- | Helper routine for @loadTSPFile@. Reads the specification section of a file. -} -readSpecification :: [String]->([Specification],[String]) -readSpecification [] = ([FAIL "seem to have run out of data, without ending the specification phase"],[]) +readSpecification :: [B.ByteString]->([Specification],[B.ByteString]) +readSpecification [] = ([FAIL $ B.pack "seem to have run out of data, without ending the specification phase"],[]) readSpecification (s:ss) = let p = readSpecificationLine s (rs,es) = readSpecification ss in case p of - ENDSPEC k -> ([USEFUL "DATA PART TYPE" k],ss) - IGNORE _ -> (p:rs,es) - FAIL _ -> (p:rs,es) - USEFUL _ _ -> (p:rs,es) + ENDSPEC k -> ([USEFUL DATAPARTTYPE k],ss) + IGNORE _ -> (p:rs,es) + FAIL _ -> (p:rs,es) + USEFUL _ _ -> (p:rs,es) + {- | Loads a TSPLIB style file. The first parameter is the internal storage type from @CombinatorialProblems.TSP@. It allows for full matrix, triangular matrix and full recalculation. If the @@ -130,80 +142,91 @@ loadTSPFile :: InternalStorage->FilePath->IO TSPProblem loadTSPFile storageType fName - = do rawContents<-readFile fName - let (spec,remainder) = readSpecification $ lines rawContents + = do rawContents<-B.readFile fName + let (spec,remainder) = readSpecification $ B.lines rawContents -- mapM_ print spec -- print "" let specList = map (\(USEFUL a b)->(a,b)) . filter isUsefulSpec $ spec -- print specList - let dataPart = fromJust $ lookup "DATA PART TYPE" specList - let numNodes = read $ fromJust $ lookup "Dimension" specList - case dataPart of - "NODE COORD" -> return $ loadFromNodePositions storageType numNodes specList (takeWhile (/="EOF") remainder) - "EDGE WEIGHT" -> return $ loadFromMatrix storageType numNodes specList (takeWhile (/="EOF") remainder) - _ -> error "Unsupported data section" + let dataPart = fromJust $ lookup DATAPARTTYPE specList + let numNodes = fst . fromJust . B.readInt . fromJust $ lookup DIMENSION specList + if dataPart == nodeCoordConst + then return $ loadFromNodePositions storageType numNodes specList (myEOF remainder) + else if dataPart == edgeWeightConst + then return $ loadFromMatrix storageType numNodes specList (myEOF remainder) + else error "Unsupported data section" + where + myEOF = takeWhile (/= (B.pack "EOF")) {- | Helper routine for @loadTSPFile@. This assumes the input is just points and the distances must be calculated. -} -loadFromNodePositions :: InternalStorage->Int->[(String,String)]->[String]->TSPProblem +loadFromNodePositions :: InternalStorage->Int->[(SpecificationName,B.ByteString)]->[B.ByteString]->TSPProblem loadFromNodePositions storageType numCities spec d - = let d' = map ((\[a,b]->(a,b)) . (map readF) . (drop 1) . words) d - posArr = A.listArray (0 , numCities-1) d' + = let d' = map ((map readF) . (drop 1) . B.words) d + posArrA = U.listArray (0 , numCities-1) (map head d') + posArrB = U.listArray (0 , numCities-1) (map last d') cities = [0 ..(numCities-1)] - explicit = A.listArray (0,numCities*numCities-1) [realToFrac $ distFunc (posArr A.! a) (posArr A.! b) | a<-cities,b<-cities] - triangular = A.listArray (0,sum [0..numCities]) [realToFrac $ distFunc (posArr A.! a) (posArr A.! b) | a<-cities,b<-[0..a]] - + explicit = U.listArray (0,numCities*numCities-1) + [unwrappedFP $ distFunc (posArrA A.! a) (posArrB A.! a) (posArrA A.! b) (posArrB A.! b) | a<-cities,b<-cities] + triangular = U.listArray (0,sum [0..numCities]) + [unwrappedFP $ distFunc (posArrA A.! a) (posArrB A.! a) (posArrA A.! b) (posArrB A.! b) | a<-cities,b<-[0..a]] + p = case storageType of - ExplicitMatrix -> \x y->explicit A.! (x * numCities + y) - TriangularMatrix -> (\x y->let x' = min x y; y' = max x y in triangular A.! (div (y'*y'+y') 2 + x')) - Recomputation -> \a b->realToFrac $ distFunc (posArr A.! a) (posArr A.! b) - in TSPProblem 0 M.empty p numCities M.empty M.empty + ExplicitMatrix -> \x y->FP $ explicit A.! (x * numCities + y) + TriangularMatrix -> (\x y->let x' = min x y; y' = max x y in FP $ triangular A.! (div (y'*y'+y') 2 + x')) + Recomputation -> \a b->realToFrac $ distFunc (posArrA A.! a) (posArrB A.! a) (posArrA A.! b) (posArrB A.! b) + in TSPProblem 0 p numCities IM.empty IM.empty where - readF = read :: (String->Double) - distanceFunctionSpec = fromJust $ lookup "EdgeWeightType" spec - distFunc = case distanceFunctionSpec of - "GEO" -> geoDistance - "EUC_2D" -> euclidianDistance - "ATT" -> pseudoEuclideanDistance - "CEIL_2D"-> euclidianDistanceCeil - _ -> error $ "unsupported distance function : "++distanceFunctionSpec + readF :: B.ByteString->Double + readF = fst . fromJust . BL.readDouble -- read . B.unpack + distanceFunctionSpec = fromJust $ lookup EDGEWEIGHTTYPE spec + distFunc = if distanceFunctionSpec == (B.pack "GEO") + then geoDistance + else if distanceFunctionSpec == (B.pack "EUC_2D") + then euclidianDistance + else if distanceFunctionSpec == (B.pack "ATT") + then pseudoEuclideanDistance + else if distanceFunctionSpec == (B.pack "CEIL_2D") + then euclidianDistanceCeil + else error $ "unsupported distance function : "++(show distanceFunctionSpec) {- | Helper routine for @loadTSPFile@. This assumes the input data is a matrix of some form, and loads it. -} -loadFromMatrix :: InternalStorage->Int->[(String,String)]->[String]->TSPProblem +loadFromMatrix :: InternalStorage->Int->[(SpecificationName,B.ByteString)]->[B.ByteString]->TSPProblem loadFromMatrix Recomputation _ _ _ = error "Cannot load matrix and store in recomputation form" loadFromMatrix storageType numCities spec d - | distanceFunctionSpec /= "EXPLICIT" = error "loading from non explicit matrix? (does not make sense)" - | storageType == TriangularMatrix = TSPProblem 0 M.empty (\x y->let x' = min x y; y' = max x y in triangularArray A.! (div (y'*y'+y') 2 + x')) numCities M.empty M.empty - | storageType == ExplicitMatrix = TSPProblem 0 M.empty (\x y->explicitArray A.! (y * numCities + x)) numCities M.empty M.empty + | distanceFunctionSpec /= B.pack "EXPLICIT" = error "loading from non explicit matrix? (does not make sense)" + | storageType == TriangularMatrix = TSPProblem 0 (\x y->let x' = min x y; y' = max x y in FP $ triangularArray A.! (div (y'*y'+y') 2 + x')) numCities IM.empty IM.empty + | storageType == ExplicitMatrix = TSPProblem 0 (\x y->FP $ explicitArray A.! (y * numCities + x)) numCities IM.empty IM.empty where - readF = realToFrac . (read :: (String->Double)) - distanceFunctionSpec = fromJust $ lookup "EdgeWeightType" spec - inputNumberSequence = concatMap ((map readF) . words) d -- not entirely trusting line breaks in file format, so turning into list of numbers, and putting in coords later + readF = unwrappedFP . (read :: String->Double) . B.unpack + distanceFunctionSpec = fromJust $ lookup EDGEWEIGHTTYPE spec + inputNumberSequence = concatMap ((map readF) . B.words) d -- not entirely trusting line breaks in file format, so turning into list of numbers, and putting in coords later cities = [0 ..(numCities-1)] blankMatrix = foldl' (\m d->M.insert (d,d) 0 m) M.empty cities fillPair m ((a,b),c) = M.insert (b,a) c $ (M.insert (a,b) c m) makeFromTri = foldl' fillPair blankMatrix - loadedMap = case fromJust $ lookup "EdgeWeightFormat" spec of - "FULL_MATRIX" -> foldl' (\m (d,c)->M.insert d c m) M.empty (zip [(a,b) | a<-cities,b<-cities] inputNumberSequence) - "UPPER_ROW" -> makeFromTri $ zip [(a,b) | a<-cities,b<-[a..(numCities - 1)],a/=b] inputNumberSequence - "LOWER_ROW" -> makeFromTri $ zip [(a,b) | a<-cities,b<-[0..a],a/=b] inputNumberSequence - "UPPER_DIAG_ROW" -> makeFromTri $ zip [(a,b) | a<-cities,b<-[a..(numCities - 1)]] inputNumberSequence - "LOWER_DIAG_ROW" -> makeFromTri $ zip [(a,b) | a<-cities,b<-[0..a]] inputNumberSequence + loadedMap = makeWeightsInternal (fromJust $ lookup EDGEWEIGHTFORMAT spec) + makeWeightsInternal inp + | B.pack "FULL_MATRIX" == inp = foldl' (\m (d,c)->M.insert d c m) M.empty (zip [(a,b) | a<-cities,b<-cities] inputNumberSequence) + | B.pack "UPPER_ROW" == inp = makeFromTri $ zip [(a,b) | a<-cities,b<-[a..(numCities - 1)],a/=b] inputNumberSequence + | B.pack "LOWER_ROW" == inp = makeFromTri $ zip [(a,b) | a<-cities,b<-[0..a],a/=b] inputNumberSequence + | B.pack "UPPER_DIAG_ROW" == inp = makeFromTri $ zip [(a,b) | a<-cities,b<-[a..(numCities - 1)]] inputNumberSequence + | B.pack "LOWER_DIAG_ROW" == inp = makeFromTri $ zip [(a,b) | a<-cities,b<-[0..a]] inputNumberSequence - "UPPER_COL" -> makeFromTri $ zip [(b,a) | a<-cities,b<-[a..(numCities - 1)],a/=b] inputNumberSequence - "LOWER_COL" -> makeFromTri $ zip [(b,a) | a<-cities,b<-[0..a],a/=b] inputNumberSequence - "UPPER_DIAG_COL" -> makeFromTri $ zip [(b,a) | a<-cities,b<-[a..(numCities - 1)]] inputNumberSequence - "LOWER_DIAG_COL" -> makeFromTri $ zip [(b,a) | a<-cities,b<-[0..a]] inputNumberSequence + | B.pack "UPPER_COL" == inp = makeFromTri $ zip [(b,a) | a<-cities,b<-[a..(numCities - 1)],a/=b] inputNumberSequence + | B.pack "LOWER_COL" == inp = makeFromTri $ zip [(b,a) | a<-cities,b<-[0..a],a/=b] inputNumberSequence + | B.pack "UPPER_DIAG_COL" == inp = makeFromTri $ zip [(b,a) | a<-cities,b<-[a..(numCities - 1)]] inputNumberSequence + | B.pack "LOWER_DIAG_COL" == inp = makeFromTri $ zip [(b,a) | a<-cities,b<-[0..a]] inputNumberSequence - explicitArray = A.listArray (0,numCities*numCities-1) [loadedMap M.! (a,b) | a<-cities,b<-cities] - triangularArray = A.listArray (0,sum [0..numCities]) [loadedMap M.! (a,b) | a<-cities,b<-[0..a]] + explicitArray = U.listArray (0,numCities*numCities-1) [loadedMap M.! (a,b) | a<-cities,b<-cities] + triangularArray = U.listArray (0,sum [0..numCities]) [loadedMap M.! (a,b) | a<-cities,b<-[0..a]] diff --git a/FileFormat/TSPLIB.o b/FileFormat/TSPLIB.o new file mode 100644 Binary files /dev/null and b/FileFormat/TSPLIB.o differ diff --git a/FormatDescriptions/tim_file_format.html b/FormatDescriptions/tim_file_format.html new file mode 100644 --- /dev/null +++ b/FormatDescriptions/tim_file_format.html @@ -0,0 +1,406 @@ + + + + + + + + + + + + + + + +Input Format + + + + + + + + + + + + + +
+

Input + Format

+

The problem + instance files have the following format (all numbers are integers, all intra-line + separators are spaces):

+
    +
  • +

    First line:
    + Number of events, number of rooms, number of features, number of students. +

    +
    • +
  • +

    One line for each room: +
    + Roomsize.

    +
    • +
  • +

    One line for each student/event: +
    + A zero or one. Zero means that the student does NOT attend the event, + one means that he DOES attend the event.
    + In the order of these the event changes more quickly.
    + For example, if there were $3$students and $4$events then the following:

    +
    • +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

0

1

0

0

1

1

0

0

0

0

1

0

+

              + would give this attends matrix:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

 

 

 

event

 

                

 

 

0

1

0

0

student

 

1

1

0

0

 

 

0

0

1

0

+

             Meaning:

+

       the first student attends the + second event
+        the + second student attends the first and second events
+        the + third student attends the third event

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

0

1

0

0

1

1

0

0

0

0

1

0

+

        would give this roomfeatures + matrix:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

 

 

 

feature

 

                

 

 

0

1

0

0

room

 

1

1

0

0

 

 

0

0

1

0

+

       Meaning:

+

       the first room satisfies the + second feature
+        the + second room satisfies the first and second features
+        the + third room satisfies the third feature

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

0

1

0

0

1

1

0

0

0

0

1

0

+

       would give this eventfeatures + matrix:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

 

 

 

feature

 

                

 

 

0

1

0

0

event

 

1

1

0

0

 

 

0

0

1

0

+

       Meaning:

+

       the first event requires the + second feature
+        the + second event requires the first and second features
+        the + third event requires the third feature

+
+ + diff --git a/Test.csv b/Test.csv new file mode 100644 --- /dev/null +++ b/Test.csv @@ -0,0 +1,637 @@ +Number Of Events,400 +Number Of Rooms,10 +Number Of Features,10 +Number Of People,200 +Slots Per Day,9 +Days,5 + +Room Sizes +Room 0,10 +Room 1,10 +Room 2,10 +Room 3,10 +Room 4,11 +Room 5,11 +Room 6,11 +Room 7,10 +Room 8,11 +Room 9,10 + +Student Event Table 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b/TestCode.hs new file mode 100644 --- /dev/null +++ b/TestCode.hs @@ -0,0 +1,59 @@ +import CombinatorialOptimisation.TIM +import FileFormat.TIM + +import System.Random +import Data.List + +main :: IO() +main = do p<-loadTIMFileRaw "../exampleProblems/TT2002/competition01.tim" + writeFile "Test.csv" $ rawToCSV p + p'<-loadTIMFile "../exampleProblems/TT2002/competition01.tim" + writeFile "Test2.csv" $ viewConstrainedProblem p' + --putStrLn $ timeTableDetailsAsCSV p' + gen<-newStdGen + let p'' = stochasticBasic p' gen + putStrLn $ timeTableDetailsAsCSV p'' + print p'' + + userIn<-getLine + let p'''=descheduleEvent (read userIn) p'' + putStrLn $ timeTableDetailsAsCSV p''' + print p'' + print p''' + + -- mapM_ print $ take 2000000 $ randomWalk gen p'' + -- print $ unscheduledEvents p' + +stochasticBasic t g = foldl (\c (a,b,d)->schedule a b d c) t $ zip3 randomTimes randomRooms (unscheduledEvents t) + where + (g1,g2) = split g + randomTimes = randomRs (0,numberOfTimeSlots t -1) g1 + randomRooms = randomRs (0,numberOfRooms t -1) g2 + +perterb :: RandomGen g=>Int->g->TimeTable->TimeTable +perterb i g t = stochasticBasic finalT finalG + where + baseLimit = length (currentlyScheduledEvents t)-1 + (finalT,finalG) = descheduleSome i baseLimit g t + descheduleSome 0 _ g' t' = (t',g') + descheduleSome n r g' t' = let (v,g'') = randomR (0,r) g' + k = currentlyScheduledEvents t' !! v + in descheduleSome (n-1) (r-1) g'' (descheduleEvent k t') + +randomWalk :: RandomGen g=>g->TimeTable->[TimeTable] +randomWalk g t = let gs = unfoldr (Just . split) g + as = t : zipWith f as ps + ps = zipWith (perterb 3) gs as + in as + where + f a b = let aV = ittcObjectiveValue a + bV = ittcObjectiveValue b + in if aV>bV then a else b + + + + + + + + diff --git a/TestTSP.hs b/TestTSP.hs new file mode 100644 --- /dev/null +++ b/TestTSP.hs @@ -0,0 +1,19 @@ +import FileFormat.TSPLIB +import CombinatorialOptimisation.TSP +import System.Random + + +main = do g<-newStdGen + let prob = makeEuclideanTSPMap ExplicitMatrix (0,100) (0,100) 8 g + let b = setRoute [0..7] prob + print b + print $ kFragments [2,4,7] b + print $ exhaustiveFragmentRebuild True b . kFragments [2,4,7] $ b + + + +{- x <- loadTSPFile TriangularMatrix "fl417.tsp" + -- print $ showEdgeWeights x + let x' = randomiseRoute (mkStdGen 417) x + print $ (\(TSPProblem m _ _ _ _ _)->m) x' -} + diff --git a/combinatorial-problems.cabal b/combinatorial-problems.cabal --- a/combinatorial-problems.cabal +++ b/combinatorial-problems.cabal @@ -1,5 +1,5 @@ Name: combinatorial-problems -Version: 0.0.4 +Version: 0.0.5 Synopsis: A number of data structures to represent and allow the manipulation of standard combinatorial problems, used as test problems in computer science. Description: In computer science there are a number of standard test problems that are used for testing algorithms, especially those related to Artificial Intelligence and Operations Research. Online there are a number @@ -40,5 +40,7 @@ random >= 1.0.0.1, containers >= 0.2.0.1, array >= 0.2.0.0, - parsec >= 3.1.1 + parsec >= 3.1.1, + bytestring >= 0.9.1.10, + bytestring-lexing >=0.2.1 extensions: diff --git a/dist/build/CombinatorialOptimisation/SAT.hi b/dist/build/CombinatorialOptimisation/SAT.hi new file mode 100644 Binary files /dev/null and b/dist/build/CombinatorialOptimisation/SAT.hi differ diff --git a/dist/build/CombinatorialOptimisation/SAT.o b/dist/build/CombinatorialOptimisation/SAT.o new file mode 100644 Binary files /dev/null and b/dist/build/CombinatorialOptimisation/SAT.o differ diff --git a/dist/build/CombinatorialOptimisation/SAT.p_hi b/dist/build/CombinatorialOptimisation/SAT.p_hi new file mode 100644 Binary files /dev/null and b/dist/build/CombinatorialOptimisation/SAT.p_hi differ diff --git a/dist/build/CombinatorialOptimisation/SAT.p_o b/dist/build/CombinatorialOptimisation/SAT.p_o new file mode 100644 Binary files /dev/null and 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b/dist/build/autogen/Paths_combinatorial_problems.hs new file mode 100644 --- /dev/null +++ b/dist/build/autogen/Paths_combinatorial_problems.hs @@ -0,0 +1,32 @@ +module Paths_combinatorial_problems ( + version, + getBinDir, getLibDir, getDataDir, getLibexecDir, + getDataFileName + ) where + +import qualified Control.Exception as Exception +import Data.Version (Version(..)) +import System.Environment (getEnv) +catchIO :: IO a -> (Exception.IOException -> IO a) -> IO a +catchIO = Exception.catch + + +version :: Version +version = Version {versionBranch = [0,0,5], versionTags = []} +bindir, libdir, datadir, libexecdir :: FilePath + +bindir = "/home/richard/.cabal/bin" +libdir = "/home/richard/.cabal/lib/combinatorial-problems-0.0.5/ghc-7.4.2" +datadir = "/home/richard/.cabal/share/combinatorial-problems-0.0.5" +libexecdir = "/home/richard/.cabal/libexec" + +getBinDir, getLibDir, getDataDir, getLibexecDir :: IO FilePath +getBinDir = catchIO (getEnv "combinatorial_problems_bindir") (\_ -> return bindir) +getLibDir = catchIO (getEnv "combinatorial_problems_libdir") (\_ -> return libdir) +getDataDir = catchIO (getEnv "combinatorial_problems_datadir") (\_ -> return datadir) +getLibexecDir = catchIO (getEnv "combinatorial_problems_libexecdir") (\_ -> return libexecdir) + +getDataFileName :: FilePath -> IO FilePath +getDataFileName name = do + dir <- getDataDir + return (dir ++ "/" ++ name) diff --git a/dist/build/autogen/cabal_macros.h b/dist/build/autogen/cabal_macros.h new file mode 100644 --- /dev/null +++ b/dist/build/autogen/cabal_macros.h @@ -0,0 +1,51 @@ +/* DO NOT EDIT: This file is automatically generated by Cabal */ + +/* package array-0.4.0.0 */ +#define VERSION_array "0.4.0.0" +#define MIN_VERSION_array(major1,major2,minor) (\ + (major1) < 0 || \ + (major1) == 0 && (major2) < 4 || \ + (major1) == 0 && (major2) == 4 && (minor) <= 0) + +/* package base-4.5.1.0 */ +#define VERSION_base "4.5.1.0" +#define MIN_VERSION_base(major1,major2,minor) (\ + (major1) < 4 || \ + (major1) == 4 && (major2) < 5 || \ + (major1) == 4 && (major2) == 5 && (minor) <= 1) + +/* package bytestring-0.9.2.1 */ +#define VERSION_bytestring "0.9.2.1" +#define MIN_VERSION_bytestring(major1,major2,minor) (\ + (major1) < 0 || \ + (major1) == 0 && (major2) < 9 || \ + (major1) == 0 && (major2) == 9 && (minor) <= 2) + +/* package bytestring-lexing-0.4.0 */ +#define VERSION_bytestring_lexing "0.4.0" +#define MIN_VERSION_bytestring_lexing(major1,major2,minor) (\ + (major1) < 0 || \ + (major1) == 0 && (major2) < 4 || \ + (major1) == 0 && (major2) == 4 && (minor) <= 0) + +/* package containers-0.5.2.1 */ +#define VERSION_containers "0.5.2.1" +#define MIN_VERSION_containers(major1,major2,minor) (\ + (major1) < 0 || \ + (major1) == 0 && (major2) < 5 || \ + (major1) == 0 && (major2) == 5 && (minor) <= 2) + +/* package parsec-3.1.3 */ +#define VERSION_parsec "3.1.3" +#define MIN_VERSION_parsec(major1,major2,minor) (\ + (major1) < 3 || \ + (major1) == 3 && (major2) < 1 || \ + (major1) == 3 && (major2) == 1 && (minor) <= 3) + +/* package random-1.0.1.1 */ +#define VERSION_random "1.0.1.1" +#define MIN_VERSION_random(major1,major2,minor) (\ + (major1) < 1 || \ + (major1) == 1 && (major2) < 0 || \ + (major1) == 1 && (major2) == 0 && (minor) <= 1) + diff --git a/dist/build/libHScombinatorial-problems-0.0.5.a b/dist/build/libHScombinatorial-problems-0.0.5.a new file mode 100644 Binary files /dev/null and b/dist/build/libHScombinatorial-problems-0.0.5.a differ diff --git a/dist/package.conf.inplace b/dist/package.conf.inplace new file mode 100644 --- /dev/null +++ b/dist/package.conf.inplace @@ -0,0 +1,2 @@ +[InstalledPackageInfo {installedPackageId = InstalledPackageId "combinatorial-problems-0.0.5-inplace", sourcePackageId = PackageIdentifier {pkgName = PackageName "combinatorial-problems", pkgVersion = Version {versionBranch = [0,0,5], versionTags = []}}, license = GPL Nothing, copyright = "Copyright (c) 2011 Richard Senington", maintainer = "sc06r2s@leeds.ac.uk", author = "Richard Senington", stability = "experimental", homepage = "http://www.comp.leeds.ac.uk/sc06r2s/Projects/HaskellCombinatorialProblems", pkgUrl = "", synopsis = "A number of data structures to represent and allow the manipulation of standard combinatorial problems, used as test problems in computer science.", description = "In computer science there are a number of standard test problems that are used for testing algorithms,\nespecially those related to Artificial Intelligence and Operations Research. Online there are a number\nof repositories for collections of known interesting problems, for example the TSPLIB at\n and the SATLIB at\n.\n\nThis library seeks to provide implementations of data structures to store these problems, along with\nfunctions for manipulating the problems and routines to load problem files from various sources.\n\nAt present it supports TSP\\/TSPLIB, SAT\\/SATLIB and TIM (format used by the International Timetabling Competition,\nwhich has been run twice at current date), however it is hoped that the loading routines\ncan be expanded and the range of problems expanded to cover problems like scheduling and more general timetabling.\nThe internal data structures make heavy use of the @Data.Map@ library and @Data.Array@. It is not currently\nusing unboxed values. The library does not use the @bytestring@ library for loading and saving data either,\nwhich will probably need to be changed later.", category = "Optimisation", exposed = True, exposedModules = ["FileFormat.SATLIB","FileFormat.TSPLIB","FileFormat.TIM","CombinatorialOptimisation.SAT","CombinatorialOptimisation.TSP","CombinatorialOptimisation.TSP.FixedPoint","CombinatorialOptimisation.TIM"], hiddenModules = [], trusted = False, importDirs = ["/home/richard/Documents/CombinatorialProblems/combinatorial-problems-0.0.5/dist/build"], libraryDirs = ["/home/richard/Documents/CombinatorialProblems/combinatorial-problems-0.0.5/dist/build"], hsLibraries = ["HScombinatorial-problems-0.0.5"], extraLibraries = [], extraGHCiLibraries = [], includeDirs = [], includes = [], depends = [InstalledPackageId "array-0.4.0.0-4f6c2a594155b0b953c1cf0f54040f61",InstalledPackageId "base-4.5.1.0-6909ea031307e047b8ba5b23968c534b",InstalledPackageId 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