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SandBoxLinearProgramming

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Editor: pagani Time: 2018/07/16 19:35:26 GMT+0
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changed:
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\begin{spad}
)abbrev package LINPROG LinearProgramming
++ Author: Kurt Pagani
++ Date Created: Sun Jun 03 02:05:55 CEST 2018
++ License: BSD
++ References:
++ Description:
++ TODO: description, more in test_linprog, eps, tol    
++ IDEA: linSolve standard method, try LU from jet
++ LINPROG  
++
LinearProgramming() : Exports == Implementation where
  
  R ==> Float
  PI ==> PositiveInteger
  NNI ==> NonNegativeInteger
  MATR ==> Matrix R
  VECR ==> Vector R
  LI ==> List Integer
  RESR ==> Record(x:VECR,f:R,itn:NNI)
  RESRS ==> Record(X:VECR,objVal:R,Basis:LI)
  RLUP ==> Record(L:MATR,U:MATR,P:MATR)
  RXP ==> Record(X:VECR,P:MATR)
  
  Exports ==  with
    
    revisedSimplex : (MATR,VECR,VECR,LI) -> RESRS
    revisedSimplexLU : (MATR,VECR,VECR,LI) -> RESRS
    luDecompose : MATR -> RLUP
    luSolve : (MATR,VECR) -> RXP

	
	
  Implementation ==  MATR add 
  
    eps:R:=0.00001
    zeroTol:R:= 0.00001
  
    revisedSimplex(A:MATR,b:VECR,c:VECR,B:LI):RESRS ==
      numRows:PI := #b ::PI
      numVars:PI := #c ::PI
      --zeroTol:R:= 0.00001
      N:LI := [i for i in 1..numVars | not member?(i,B)]
      --N:LI:=setDifference([i for i in 1..numVars],B)
      RA:LI:=[i for i in 1..nrows(A)]
      AB:MATR:=A(RA,B) 
      AN:MATR:=A(RA,N)
      numNonbasicVars:=#N
      cN := vector [c.i for i in N]
      cB := vector [c.i for i in B]
      IAB:Union(MATR,"failed"):=inverse(AB)
      if IAB case MATR then
        bBAR:VECR := IAB*b
      else
        error "AB not invertible"
      objVal := dot(cB,bBAR)
      negRedCost := -1.0
      while negRedCost < 0.0 repeat
        IAB:Union(MATR,"failed"):=inverse(AB)
        if IAB case MATR then
          wN:VECR := cN - (cB*IAB)*AN
        else
          error "AB not invertible"
        --
        negRedCostIdx:NNI := 0
        negRedCost := 0.0
        --
        for k in 1..numNonbasicVars repeat
          if wN.k < -zeroTol then
            negRedCost := wN.k
            --record the index
            negRedCostIdx := k
            break
        --
        if negRedCost < 0.0 then
          IAB:Union(MATR,"failed"):=inverse(AB)
          if IAB case MATR then
            aBAR:VECR := IAB*column(AN,negRedCostIdx)
          else
            error "AB not invertible"
          minRatioVal := 1.0/zeroTol --inf
          minRatioIdx := 0
          --
          for k in 1..numRows repeat
            if aBAR.k > zeroTol then
              if bBAR.k / aBAR.k < minRatioVal then
                minRatioVal := bBAR.k / aBAR.k
                --record the index
                minRatioIdx:NNI := k
          --
          bBAR := bBAR - minRatioVal * aBAR
          bBAR.minRatioIdx := minRatioVal
          --
          tmpIdx := B.minRatioIdx
          B.minRatioIdx := N.negRedCostIdx
          N.negRedCostIdx := tmpIdx
          --
          AB:MATR:=A(RA,B) 
          AN:MATR:=A(RA,N)
          cN := vector [c.i for i in N]
          cB := vector [c.i for i in B]
        X:VECR:=zero(numVars)
        for i in 1..numRows repeat
          X.(B.i) := bBAR.i
        objVal := dot(cB,bBAR)
      return [X,objVal,B]
    
    luDecompose(A:MATR):RLUP ==
      not square?(A)$MATR => error "Input matrix is not square."
      (numRows, numVars) := (nrows A, ncols A)
      U:MATR:=copy A
      LK:MATR:=zero(numRows,numRows)$MATR
      I:MATR:=diagonalMatrix(vector [1 for i in 1..numRows])
      P:MATR:=copy I
      LINV:=copy I
      RA:LI:=[i for i in 1..numRows]  
      for i in 1..numVars repeat
        perm:LI:=[m for m in 1..numRows]   -- don't use RA or i as index!!
        pivotEl := 0$R
        for j in i..numRows repeat
          if abs(U(j,i)) > eps then
            tmp := perm.i
            perm.i := perm.j
            perm.j := tmp
            U:=I(perm,RA)*U
            P:=I(perm,RA)*P
            pivotEl := U(i, i)
            break
        abs(pivotEl) <= eps => error("Matrix is singular")
        LK := I(perm,RA) * LK
        LK(i,i) := 1$R 
        LINVK := copy I
        --
        for k in i+1..numRows repeat
          if U(k, i) ~= 0$R then
            multiplier := U(k, i)/pivotEl
            U(k,RA) := U(k,RA) -  multiplier * U(i,RA)
            LK(k,i) := multiplier
            LINVK(k, i) := - multiplier
        --
        LINV := LINVK*LINV
      return [LK,U,P]
      

    luSolve(A:MATR,b:VECR):RXP ==
      not square?(A)$MATR => error "Input matrix is not square."
      (numRows, numVars) := (nrows A, ncols A)
      r:RLUP:=luDecompose(A)
      U:=copy r.U
      L:=copy r.L
      P:=copy r.P
      Y:=vector [0$R for m in 1..numRows]
      X:=vector [0$R for m in 1..numRows]
      rhs:VECR := P*b
      for i in 1..numVars repeat
        Y.i := rhs.i
        rhs := rhs - Y.i * column(L,i)
      for i in numVars..1 by -1 repeat
        X.i := Y.i / U(i,i)
        Y := Y - X.i * column(U,i)      
      return [X,P]
 
    revisedSimplexLU(A:MATR,b:VECR,c:VECR,B:LI):RESRS ==
      numRows:PI := #b ::PI
      numVars:PI := #c ::PI
      --zeroTol:R:= 0.00001
      N:LI := [i for i in 1..numVars | not member?(i,B)]
      --N:LI:=setDifference([i for i in 1..numVars],B)
      RA:LI:=[i for i in 1..nrows(A)]
      AB:MATR:=A(RA,B) 
      AN:MATR:=A(RA,N)
      numNonbasicVars:=#N
      cN := vector [c.i for i in N]
      cB := vector [c.i for i in B]
      --
      bBAR:VECR := luSolve(AB,b).X ---- luSolve
      objVal := dot(cB,bBAR)
      negRedCost := -1.0
      while negRedCost < 0.0 repeat
        u:VECR:= luSolve(transpose(AB),cB).X
        wN:VECR := cN - u*AN
        --
        negRedCostIdx:NNI := 0
        negRedCost := 0.0
        --
        for k in 1..numNonbasicVars repeat
          if wN.k < -zeroTol then
            negRedCost := wN.k
            --record the index
            negRedCostIdx := k
            break
        --
        if negRedCost < 0.0 then
         
          aBAR:VECR := luSolve(AB,column(AN,negRedCostIdx)).X
          minRatioVal := 1.0/zeroTol --inf
          minRatioIdx := 0
          --
          for k in 1..numRows repeat
            if aBAR.k > zeroTol then
              if bBAR.k / aBAR.k < minRatioVal then
                minRatioVal := bBAR.k / aBAR.k
                --record the index
                minRatioIdx:NNI := k
          --
          bBAR := bBAR - minRatioVal * aBAR
          bBAR.minRatioIdx := minRatioVal
          --
          tmpIdx := B.minRatioIdx
          B.minRatioIdx := N.negRedCostIdx
          N.negRedCostIdx := tmpIdx
          --
          AB:MATR:=A(RA,B) 
          AN:MATR:=A(RA,N)
          cN := vector [c.i for i in N]
          cB := vector [c.i for i in B]
        X:VECR:=zero(numVars)
        for i in 1..numRows repeat
          X.(B.i) := bBAR.i
        objVal := dot(cB,bBAR)
      return [X,objVal,B]
    
\end{spad}

Test flavours

\begin{axiom}
-- Unittest .....: Package LinearProgramming
-- Author .......: Kurt Pagani
-- Date .........: Sun Jun 17 02:14:10 CEST 2018

)set break resume
)expose UnittestCount UnittestAux Unittest

--)co linprog
)expose LINPROG

-- Test Suite
testsuite "Package: LinearProgramming"

-- Cases
testcase "revisedSimplex"
-- testEquals("", "")

A:=matrix [[0.7,1.0,1.0,0.0,0.0,0.0],[0.5,(5/6)::Float,0.0,1.0,0.0,0.0],
           [1.0,(2/3)::Float,0.0,0.0,1.0,0.0],[0.1,0.25,0.0,0.0,0.0,1.0]]
   
c:=vector [-10.0,-9.0,0.0,0.0,0.0,0.0]
b:=vector [630.0,600.0,708.0,135.0]
B:=[3,4,5,6]

X1:Vector Float:= vector [540.0,252.0,0.0,120.0,0.0,18.0]
objVal1:Float:= - 7668.0
Basis1:List Integer:= [2,4,1,6]

eps:=0.0000000001
floatNull(v:Vector Float):Boolean == sqrt dot(v,v) <= eps 

r1:=revisedSimplex( A, b, c, B)
testEquals("floatNull(r1.X-X1)", "true")
testEquals("abs(r1.objVal-objVal1)<eps", "true")
testEquals("r1.Basis", "Basis1")

r1lu:=revisedSimplexLU( A, b, c, B)
testEquals("floatNull(r1lu.X-X1)", "true")
testEquals("abs(r1lu.objVal-objVal1)<eps", "true")
testEquals("r1lu.Basis", "Basis1")

--

---
A2 := matrix [[0,1,-1,0,0,0], [1,1,0,-1,0,0], 
               [-0.5,1,0,0,1,0],[-1,1,0,0,0,1]]

c2 := vector [2,-3,0,0,0,0]
b2 := vector [1,2,8,6] 
B2 := [1,2,5,6]

X2:= [4.0,10.0,9.0,12.0,0.0,0.0]
objVal2:= - 22.0
Basis2:= [3,2,1,4]

r2:=revisedSimplex( A2, b2, c2, B2)
testEquals("floatNull(r2.X-X2)", "true")
testEquals("abs(r2.objVal-objVal2)<eps", "true")
testEquals("r2.Basis", "Basis2")


r2lu:=revisedSimplexLU( A2, b2, c2, B2)
testEquals("floatNull(r2lu.X-X2)", "true")
testEquals("abs(r2lu.objVal-objVal2)<eps", "true")
testEquals("r2lu.Basis", "Basis2")

--

A3 := matrix [[0.4,0.5,1,0,0],[0,0.2,0,1,0],[0.6,0.3,0,0,1]]
c3 := vector [-40,-30,0,0,0]
b3 := vector [20,5,21] 
B3 := [3,4,5]

X3:= [25.0,20.0,0.0,1.0,0.0]
objVal3:= - 1600.0
Basis3:= [2,4,1]

r3:=revisedSimplex(A3, b3, c3, B3)
testEquals("floatNull(r3.X-X3)", "true")
testEquals("abs(r3.objVal-objVal3)<eps", "true")
testEquals("r3.Basis", "Basis3")

r3lu:=revisedSimplexLU(A3, b3, c3, B3)
testEquals("floatNull(r3lu.X-X3)", "true")
testEquals("abs(r3lu.objVal-objVal3)<eps", "true")
testEquals("r3lu.Basis", "Basis3")

--
A4 := matrix [[1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0],_
              [0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0],_
              [0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0],_
              [0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0],_
              [3, 0, 6, 0, 5, 0, 7, 0, 1, 0, 0, 0, 0, 0, 1, 0],_
              [0, 2, 0, 4, 0, 10, 0, 4, 0, 1, 0, 0, 0, 0, 0, 1]]

b4 := vector [1, 1, 1, 1, 13, 10]
c4 := vector [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1]
B4 := [11, 12, 13, 14, 15, 16]

X4:= [1.0, 0.0, 0.25, 0.7500000000_0000000001, 0.3, 0.7, 1.0, 0.0, 0.0, 0.0,
      0.0, 0.0, 0.0, 0.0, 0.0, 0.0]

objVal4:= 0.0
Basis4:= [1,3,6,5,7,4]

r4 := revisedSimplex( A4, b4, c4, B4)
testEquals("floatNull(r4.X-X4)", "true")
testEquals("abs(r4.objVal-objVal4)<eps", "true")
testEquals("r4.Basis", "Basis4")

r4lu := revisedSimplexLU( A4, b4, c4, B4)
testEquals("floatNull(r4lu.X-X4)", "true")
testEquals("abs(r4lu.objVal-objVal4)<eps", "true")
testEquals("r4lu.Basis", "Basis4")

--
A5 := matrix [[1, -1, 1, 0, 0], [4, 9, 0, 1, 0], [-2, 4, 0, 0, 1]]
c5 := vector [-1, -1, 0, 0, 0]
b5 := vector [2, 18, 4] 
B5 := vector [3, 4, 5]


X5 := [2.7692307692_307692308, 0.7692307692_3076923077, 0.0, 0.0,
       6.4615384615_384615385]
    
objVal5:= - 3.5384615384_615384615
Basis5:= [1,2,5]

r5 := revisedSimplex( A5, b5, c5, B5)
testEquals("floatNull(r5.X-X5)", "true")
testEquals("abs(r5.objVal-objVal5)<eps", "true")
testEquals("r5.Basis", "Basis5") 

r5lu := revisedSimplexLU( A5, b5, c5, B5)
testEquals("floatNull(r5lu.X-X5)", "true")
testEquals("abs(r5lu.objVal-objVal5)<eps", "true")
testEquals("r5lu.Basis", "Basis5") 


-- Results/Statistics
)set output algebra on
)version
)lisp (lisp-implementation-type)
)lisp (lisp-implementation-version)

statistics()
\end{axiom}

spad

)abbrev package LINPROG LinearProgramming
++ Author: Kurt Pagani
++ Date Created: Sun Jun 03 02:05:55 CEST 2018
++ License: BSD
++ References:
++ Description:
++ TODO: description, more in test_linprog, eps, tol    
++ IDEA: linSolve standard method, try LU from jet
++ LINPROG  
++
LinearProgramming() : Exports == Implementation where

  R ==> Float
  PI ==> PositiveInteger
  NNI ==> NonNegativeInteger
  MATR ==> Matrix R
  VECR ==> Vector R
  LI ==> List Integer
  RESR ==> Record(x:VECR,f:R,itn:NNI)
  RESRS ==> Record(X:VECR,objVal:R,Basis:LI)
  RLUP ==> Record(L:MATR,U:MATR,P:MATR)
  RXP ==> Record(X:VECR,P:MATR)

  Exports ==  with

    revisedSimplex : (MATR,VECR,VECR,LI) -> RESRS
    revisedSimplexLU : (MATR,VECR,VECR,LI) -> RESRS
    luDecompose : MATR -> RLUP
    luSolve : (MATR,VECR) -> RXP

  Implementation ==  MATR add 

    eps:R:=0.00001
    zeroTol:R:= 0.00001

    revisedSimplex(A:MATR,b:VECR,c:VECR,B:LI):RESRS ==
      numRows:PI := #b ::PI
      numVars:PI := #c ::PI
      --zeroTol:R:= 0.00001
      N:LI := [i for i in 1..numVars | not member?(i,B)]
      --N:LI:=setDifference([i for i in 1..numVars],B)
      RA:LI:=[i for i in 1..nrows(A)]
      AB:MATR:=A(RA,B) 
      AN:MATR:=A(RA,N)
      numNonbasicVars:=#N
      cN := vector [c.i for i in N]
      cB := vector [c.i for i in B]
      IAB:Union(MATR,"failed"):=inverse(AB)
      if IAB case MATR then
        bBAR:VECR := IAB*b
      else
        error "AB not invertible"
      objVal := dot(cB,bBAR)
      negRedCost := -1.0
      while negRedCost < 0.0 repeat
        IAB:Union(MATR,"failed"):=inverse(AB)
        if IAB case MATR then
          wN:VECR := cN - (cB*IAB)*AN
        else
          error "AB not invertible"
        --
        negRedCostIdx:NNI := 0
        negRedCost := 0.0
        --
        for k in 1..numNonbasicVars repeat
          if wN.k < -zeroTol then
            negRedCost := wN.k
            --record the index
            negRedCostIdx := k
            break
        --
        if negRedCost < 0.0 then
          IAB:Union(MATR,"failed"):=inverse(AB)
          if IAB case MATR then
            aBAR:VECR := IAB*column(AN,negRedCostIdx)
          else
            error "AB not invertible"
          minRatioVal := 1.0/zeroTol --inf
          minRatioIdx := 0
          --
          for k in 1..numRows repeat
            if aBAR.k > zeroTol then
              if bBAR.k / aBAR.k < minRatioVal then
                minRatioVal := bBAR.k / aBAR.k
                --record the index
                minRatioIdx:NNI := k
          --
          bBAR := bBAR - minRatioVal * aBAR
          bBAR.minRatioIdx := minRatioVal
          --
          tmpIdx := B.minRatioIdx
          B.minRatioIdx := N.negRedCostIdx
          N.negRedCostIdx := tmpIdx
          --
          AB:MATR:=A(RA,B) 
          AN:MATR:=A(RA,N)
          cN := vector [c.i for i in N]
          cB := vector [c.i for i in B]
        X:VECR:=zero(numVars)
        for i in 1..numRows repeat
          X.(B.i) := bBAR.i
        objVal := dot(cB,bBAR)
      return [X,objVal,B]

    luDecompose(A:MATR):RLUP ==
      not square?(A)$MATR => error "Input matrix is not square."
      (numRows, numVars) := (nrows A, ncols A)
      U:MATR:=copy A
      LK:MATR:=zero(numRows,numRows)$MATR
      I:MATR:=diagonalMatrix(vector [1 for i in 1..numRows])
      P:MATR:=copy I
      LINV:=copy I
      RA:LI:=[i for i in 1..numRows]  
      for i in 1..numVars repeat
        perm:LI:=[m for m in 1..numRows]   -- don't use RA or i as index!!
        pivotEl := 0$R
        for j in i..numRows repeat
          if abs(U(j,i)) > eps then
            tmp := perm.i
            perm.i := perm.j
            perm.j := tmp
            U:=I(perm,RA)*U
            P:=I(perm,RA)*P
            pivotEl := U(i, i)
            break
        abs(pivotEl) <= eps => error("Matrix is singular")
        LK := I(perm,RA) * LK
        LK(i,i) := 1$R 
        LINVK := copy I
        --
        for k in i+1..numRows repeat
          if U(k, i) ~= 0$R then
            multiplier := U(k, i)/pivotEl
            U(k,RA) := U(k,RA) -  multiplier * U(i,RA)
            LK(k,i) := multiplier
            LINVK(k, i) := - multiplier
        --
        LINV := LINVK*LINV
      return [LK,U,P]

    luSolve(A:MATR,b:VECR):RXP ==
      not square?(A)$MATR => error "Input matrix is not square."
      (numRows, numVars) := (nrows A, ncols A)
      r:RLUP:=luDecompose(A)
      U:=copy r.U
      L:=copy r.L
      P:=copy r.P
      Y:=vector [0$R for m in 1..numRows]
      X:=vector [0$R for m in 1..numRows]
      rhs:VECR := P*b
      for i in 1..numVars repeat
        Y.i := rhs.i
        rhs := rhs - Y.i * column(L,i)
      for i in numVars..1 by -1 repeat
        X.i := Y.i / U(i,i)
        Y := Y - X.i * column(U,i)      
      return [X,P]

    revisedSimplexLU(A:MATR,b:VECR,c:VECR,B:LI):RESRS ==
      numRows:PI := #b ::PI
      numVars:PI := #c ::PI
      --zeroTol:R:= 0.00001
      N:LI := [i for i in 1..numVars | not member?(i,B)]
      --N:LI:=setDifference([i for i in 1..numVars],B)
      RA:LI:=[i for i in 1..nrows(A)]
      AB:MATR:=A(RA,B) 
      AN:MATR:=A(RA,N)
      numNonbasicVars:=#N
      cN := vector [c.i for i in N]
      cB := vector [c.i for i in B]
      --
      bBAR:VECR := luSolve(AB,b).X ---- luSolve
      objVal := dot(cB,bBAR)
      negRedCost := -1.0
      while negRedCost < 0.0 repeat
        u:VECR:= luSolve(transpose(AB),cB).X
        wN:VECR := cN - u*AN
        --
        negRedCostIdx:NNI := 0
        negRedCost := 0.0
        --
        for k in 1..numNonbasicVars repeat
          if wN.k < -zeroTol then
            negRedCost := wN.k
            --record the index
            negRedCostIdx := k
            break
        --
        if negRedCost < 0.0 then

          aBAR:VECR := luSolve(AB,column(AN,negRedCostIdx)).X
          minRatioVal := 1.0/zeroTol --inf
          minRatioIdx := 0
          --
          for k in 1..numRows repeat
            if aBAR.k > zeroTol then
              if bBAR.k / aBAR.k < minRatioVal then
                minRatioVal := bBAR.k / aBAR.k
                --record the index
                minRatioIdx:NNI := k
          --
          bBAR := bBAR - minRatioVal * aBAR
          bBAR.minRatioIdx := minRatioVal
          --
          tmpIdx := B.minRatioIdx
          B.minRatioIdx := N.negRedCostIdx
          N.negRedCostIdx := tmpIdx
          --
          AB:MATR:=A(RA,B) 
          AN:MATR:=A(RA,N)
          cN := vector [c.i for i in N]
          cB := vector [c.i for i in B]
        X:VECR:=zero(numVars)
        for i in 1..numRows repeat
          X.(B.i) := bBAR.i
        objVal := dot(cB,bBAR)
      return [X,objVal,B]

spad

   Compiling FriCAS source code from file 
      /var/lib/zope2.10/instance/axiom-wiki/var/LatexWiki/5717432969159631359-25px001.spad
      using old system compiler.
   LINPROG abbreviates package LinearProgramming 
------------------------------------------------------------------------
   initializing NRLIB LINPROG for LinearProgramming 
   compiling into NRLIB LINPROG 
   compiling exported revisedSimplex : (Matrix Float,Vector Float,Vector Float,List Integer) -> Record(X: Vector Float,objVal: Float,Basis: List Integer)
Local variable minRatioIdx type redefined: (NonNegativeInteger) to (Float)
Time: 0.11 SEC.

   compiling exported luDecompose : Matrix Float -> Record(L: Matrix Float,U: Matrix Float,P: Matrix Float)
Time: 0.03 SEC.

   compiling exported luSolve : (Matrix Float,Vector Float) -> Record(X: Vector Float,P: Matrix Float)
Time: 0.02 SEC.

   compiling exported revisedSimplexLU : (Matrix Float,Vector Float,Vector Float,List Integer) -> Record(X: Vector Float,objVal: Float,Basis: List Integer)
Local variable minRatioIdx type redefined: (NonNegativeInteger) to (Float)
Time: 0.04 SEC.

(time taken in buildFunctor:  0)

;;;     ***       |LinearProgramming| REDEFINED

;;;     ***       |LinearProgramming| REDEFINED
Time: 0 SEC.

   Warnings: 
      [1] revisedSimplex:  negRedCostIdx has no value
      [2] revisedSimplex:  minRatioIdx has no value
      [3] revisedSimplex:  bBAR has no value
      [4] revisedSimplex:  X has no value
      [5] luDecompose:  U has no value
      [6] luDecompose:  LK has no value
      [7] luDecompose:  P has no value
      [8] luSolve:  U has no value
      [9] luSolve:  L has no value
      [10] luSolve:  P has no value
      [11] revisedSimplexLU:  negRedCostIdx has no value
      [12] revisedSimplexLU:  minRatioIdx has no value
      [13] revisedSimplexLU:  bBAR has no value
      [14] revisedSimplexLU:  X has no value

   Cumulative Statistics for Constructor LinearProgramming
      Time: 0.20 seconds

--------------non extending category----------------------
.. LinearProgramming of cat 
(CATEGORY |package|
 (SIGNATURE |revisedSimplex|
  ((|Record| (|:| X (|Vector| (|Float|))) (|:| |objVal| (|Float|))
             (|:| |Basis| (|List| (|Integer|))))
   (|Matrix| (|Float|)) (|Vector| (|Float|)) (|Vector| (|Float|))
   (|List| (|Integer|))))
 (SIGNATURE |revisedSimplexLU|
  ((|Record| (|:| X (|Vector| (|Float|))) (|:| |objVal| (|Float|))
             (|:| |Basis| (|List| (|Integer|))))
   (|Matrix| (|Float|)) (|Vector| (|Float|)) (|Vector| (|Float|))
   (|List| (|Integer|))))
 (SIGNATURE |luDecompose|
  ((|Record| (|:| L (|Matrix| (|Float|))) (|:| U (|Matrix| (|Float|)))
             (|:| P (|Matrix| (|Float|))))
   (|Matrix| (|Float|))))
 (SIGNATURE |luSolve|
  ((|Record| (|:| X (|Vector| (|Float|))) (|:| P (|Matrix| (|Float|))))
   (|Matrix| (|Float|)) (|Vector| (|Float|)))))   has no 
(|MatrixCategory| (|Float|) (|Vector| (|Float|)) (|Vector| (|Float|)))    finalizing NRLIB LINPROG 
   Processing LinearProgramming for Browser database:
--------constructor---------
--->-->LinearProgramming((revisedSimplex ((Record (: X (Vector (Float))) (: objVal (Float)) (: Basis (List (Integer)))) (Matrix (Float)) (Vector (Float)) (Vector (Float)) (List (Integer))))): Not documented!!!!
--->-->LinearProgramming((revisedSimplexLU ((Record (: X (Vector (Float))) (: objVal (Float)) (: Basis (List (Integer)))) (Matrix (Float)) (Vector (Float)) (Vector (Float)) (List (Integer))))): Not documented!!!!
--->-->LinearProgramming((luDecompose ((Record (: L (Matrix (Float))) (: U (Matrix (Float))) (: P (Matrix (Float)))) (Matrix (Float))))): Not documented!!!!
--->-->LinearProgramming((luSolve ((Record (: X (Vector (Float))) (: P (Matrix (Float)))) (Matrix (Float)) (Vector (Float))))): Not documented!!!!
; compiling file "/var/aw/var/LatexWiki/LINPROG.NRLIB/LINPROG.lsp" (written 04 APR 2022 08:23:31 PM):

; /var/aw/var/LatexWiki/LINPROG.NRLIB/LINPROG.fasl written
; compilation finished in 0:00:00.279
------------------------------------------------------------------------
   LinearProgramming is now explicitly exposed in frame initial 
   LinearProgramming will be automatically loaded when needed from 
      /var/aw/var/LatexWiki/LINPROG.NRLIB/LINPROG

Test flavours

fricas -- Unittest .....: Package LinearProgramming

Author .......: Kurt Pagani -- Date .........: Sun Jun 17 02:14:10 CEST 2018

fricas

)set break resume

fricas

)expose UnittestCount UnittestAux Unittest

   UnittestCount is now explicitly exposed in frame initial 
   UnittestAux is now explicitly exposed in frame initial 
   Unittest is now explicitly exposed in frame initial 

--)co linprog

fricas

)expose LINPROG

   LinearProgramming is already explicitly exposed in frame initial 

-- Test Suite
testsuite "Package: LinearProgramming"

   All user variables and function definitions have been cleared.
   WARNING: string for testsuite should have less than 15 characters!

Type: Void

fricas

-- Cases
testcase "revisedSimplex"

   All user variables and function definitions have been cleared.

Type: Void

fricas

-- testEquals("", "")

A:=matrix [[0.7,1.0,1.0,0.0,0.0,0.0],[0.5,(5/6)::Float,0.0,1.0,0.0,0.0],
           [1.0,(2/3)::Float,0.0,0.0,1.0,0.0],[0.1,0.25,0.0,0.0,0.0,1.0]]

$\label{eq1}\left[ \begin{array}{cccccc} {0.7}&{1.0}&{1.0}&{0.0}&{0.0}&{0.0} \ {0.5}&{0.8333333333 \ 3333333333}&{0.0}&{1.0}&{0.0}&{0.0} \ {1.0}&{0.6666666666 \ 6666666667}&{0.0}&{0.0}&{1.0}&{0.0} \ {0.1}&{0.25}&{0.0}&{0.0}&{0.0}&{1.0}$

(1)

Type: Matrix(Float)

fricas

c:=vector [-10.0,-9.0,0.0,0.0,0.0,0.0]

$\label{eq2}\left[ -{10.0}, \: -{9.0}, \:{0.0}, \:{0.0}, \:{0.0}, \:{0.0}\right]$

(2)

Type: Vector(Float)

fricas

b:=vector [630.0,600.0,708.0,135.0]

$\label{eq3}\left[{630.0}, \:{600.0}, \:{708.0}, \:{135.0}\right]$

(3)

Type: Vector(Float)

fricas

B:=[3,4,5,6]

$\label{eq4}\left[ 3, \: 4, \: 5, \: 6 \right]$

(4)

Type: List(PositiveInteger?)

fricas

X1:Vector Float:= vector [540.0,252.0,0.0,120.0,0.0,18.0]

$\label{eq5}\left[{540.0}, \:{252.0}, \:{0.0}, \:{120.0}, \:{0.0}, \:{18.0}\right]$

(5)

Type: Vector(Float)

fricas

objVal1:Float:= - 7668.0

$\label{eq6}-{7668.0}$

(6)

Type: Float

fricas

Basis1:List Integer:= [2,4,1,6]

$\label{eq7}\left[ 2, \: 4, \: 1, \: 6 \right]$

(7)

Type: List(Integer)

fricas

eps:=0.0000000001

$\label{eq8}0.1 E - 9$

(8)

Type: Float

fricas

floatNull(v:Vector Float):Boolean == sqrt dot(v,v) <= eps 

   Function declaration floatNull : Vector(Float) -> Boolean has been 
      added to workspace.

Type: Void

fricas

r1:=revisedSimplex( A, b, c, B)

$\label{eq9}\begin{array}{@{}l} \displaystyle \left[{X ={\left[{540.0}, \:{252.0}, \:{0.0}, \:{120.0}, \:{0.0}, \:{18.0}\right]}}, \:{objVal = -{7668.0}}, \: \right. \ \ \displaystyle \left.{\hbox{\axiomType{Basis}\ } ={\left[ 2, \: 4, \: 1, \: 6 \right]}}\right]$

(9)

Type: Record(X: Vector(Float),objVal: Float,Basis: List(Integer))

fricas

testEquals("floatNull(r1.X-X1)", "true")

fricas

Compiling function floatNull with type Vector(Float) -> Boolean

Type: Void

fricas

testEquals("abs(r1.objVal-objVal1)<eps", "true")

Type: Void

fricas

testEquals("r1.Basis", "Basis1")

Type: Void

fricas

r1lu:=revisedSimplexLU( A, b, c, B)

$\label{eq10}\begin{array}{@{}l} \displaystyle \left[{X ={\left[{540.0}, \:{252.0}, \:{0.0}, \:{120.0}, \:{0.0}, \:{18.0}\right]}}, \:{objVal = -{7668.0}}, \: \right. \ \ \displaystyle \left.{\hbox{\axiomType{Basis}\ } ={\left[ 2, \: 4, \: 1, \: 6 \right]}}\right]$

(10)

Type: Record(X: Vector(Float),objVal: Float,Basis: List(Integer))

fricas

testEquals("floatNull(r1lu.X-X1)", "true")

Type: Void

fricas

testEquals("abs(r1lu.objVal-objVal1)<eps", "true")

Type: Void

fricas

testEquals("r1lu.Basis", "Basis1")

Type: Void

fricas

--

---
A2 := matrix [[0,1,-1,0,0,0], [1,1,0,-1,0,0], 
               [-0.5,1,0,0,1,0],[-1,1,0,0,0,1]]

$\label{eq11}\left[ \begin{array}{cccccc} {0.0}&{1.0}& -{1.0}&{0.0}&{0.0}&{0.0} \ {1.0}&{1.0}&{0.0}& -{1.0}&{0.0}&{0.0} \ -{0.5}&{1.0}&{0.0}&{0.0}&{1.0}&{0.0} \ -{1.0}&{1.0}&{0.0}&{0.0}&{0.0}&{1.0}$

(11)

Type: Matrix(Float)

fricas

c2 := vector [2,-3,0,0,0,0]

$\label{eq12}\left[ 2, \: - 3, \: 0, \: 0, \: 0, \: 0 \right]$

(12)

Type: Vector(Integer)

fricas

b2 := vector [1,2,8,6]

$\label{eq13}\left[ 1, \: 2, \: 8, \: 6 \right]$

(13)

Type: Vector(PositiveInteger?)

fricas

B2 := [1,2,5,6]

$\label{eq14}\left[ 1, \: 2, \: 5, \: 6 \right]$

(14)

Type: List(PositiveInteger?)

fricas

X2:= [4.0,10.0,9.0,12.0,0.0,0.0]

$\label{eq15}\left[{4.0}, \:{10.0}, \:{9.0}, \:{12.0}, \:{0.0}, \:{0.0}\right]$

(15)

Type: List(Float)

fricas

objVal2:= - 22.0

$\label{eq16}-{22.0}$

(16)

Type: Float

fricas

Basis2:= [3,2,1,4]

$\label{eq17}\left[ 3, \: 2, \: 1, \: 4 \right]$

(17)

Type: List(PositiveInteger?)

fricas

r2:=revisedSimplex( A2, b2, c2, B2)

$\label{eq18}\begin{array}{@{}l} \displaystyle \left[{X ={\left[{4.0}, \:{10.0}, \:{9.0}, \:{12.0}, \:{0.0}, \:{0.0}\right]}}, \:{objVal = -{22.0}}, \: \right. \ \ \displaystyle \left.{\hbox{\axiomType{Basis}\ } ={\left[ 3, \: 2, \: 1, \: 4 \right]}}\right]$

(18)

Type: Record(X: Vector(Float),objVal: Float,Basis: List(Integer))

fricas

testEquals("floatNull(r2.X-X2)", "true")

Type: Void

fricas

testEquals("abs(r2.objVal-objVal2)<eps", "true")

Type: Void

fricas

testEquals("r2.Basis", "Basis2")

Type: Void

fricas

r2lu:=revisedSimplexLU( A2, b2, c2, B2)

$\label{eq19}\begin{array}{@{}l} \displaystyle \left[{X ={\left[{4.0}, \:{10.0}, \:{9.0}, \:{12.0}, \:{0.0}, \:{0.0}\right]}}, \:{objVal = -{22.0}}, \: \right. \ \ \displaystyle \left.{\hbox{\axiomType{Basis}\ } ={\left[ 3, \: 2, \: 1, \: 4 \right]}}\right]$

(19)

Type: Record(X: Vector(Float),objVal: Float,Basis: List(Integer))

fricas

testEquals("floatNull(r2lu.X-X2)", "true")

Type: Void

fricas

testEquals("abs(r2lu.objVal-objVal2)<eps", "true")

Type: Void

fricas

testEquals("r2lu.Basis", "Basis2")

Type: Void

fricas

--

A3 := matrix [[0.4,0.5,1,0,0],[0,0.2,0,1,0],[0.6,0.3,0,0,1]]

$\label{eq20}\left[ \begin{array}{ccccc} {0.4}&{0.5}&{1.0}&{0.0}&{0.0} \ {0.0}&{0.2}&{0.0}&{1.0}&{0.0} \ {0.6}&{0.3}&{0.0}&{0.0}&{1.0}$

(20)

Type: Matrix(Float)

fricas

c3 := vector [-40,-30,0,0,0]

$\label{eq21}\left[ -{40}, \: -{30}, \: 0, \: 0, \: 0 \right]$

(21)

Type: Vector(Integer)

fricas

b3 := vector [20,5,21]

$\label{eq22}\left[{20}, \: 5, \:{21}\right]$

(22)

Type: Vector(PositiveInteger?)

fricas

B3 := [3,4,5]

$\label{eq23}\left[ 3, \: 4, \: 5 \right]$

(23)

Type: List(PositiveInteger?)

fricas

X3:= [25.0,20.0,0.0,1.0,0.0]

$\label{eq24}\left[{25.0}, \:{20.0}, \:{0.0}, \:{1.0}, \:{0.0}\right]$

(24)

Type: List(Float)

fricas

objVal3:= - 1600.0

$\label{eq25}-{1600.0}$

(25)

Type: Float

fricas

Basis3:= [2,4,1]

$\label{eq26}\left[ 2, \: 4, \: 1 \right]$

(26)

Type: List(PositiveInteger?)

fricas

r3:=revisedSimplex(A3, b3, c3, B3)

$\label{eq27}\begin{array}{@{}l} \displaystyle \left[{X ={\left[{25.0}, \:{20.0}, \:{0.0}, \:{1.0}, \:{0.0}\right]}}, \:{objVal = -{1600.0}}, \: \right. \ \ \displaystyle \left.{\hbox{\axiomType{Basis}\ } ={\left[ 2, \: 4, \: 1 \right]}}\right]$

(27)

Type: Record(X: Vector(Float),objVal: Float,Basis: List(Integer))

fricas

testEquals("floatNull(r3.X-X3)", "true")

Type: Void

fricas

testEquals("abs(r3.objVal-objVal3)<eps", "true")

Type: Void

fricas

testEquals("r3.Basis", "Basis3")

Type: Void

fricas

r3lu:=revisedSimplexLU(A3, b3, c3, B3)

$\label{eq28}\begin{array}{@{}l} \displaystyle \left[{X ={\left[{25.0}, \:{20.0}, \:{0.0}, \:{0.9999999999 \_ 9999999997}, \:{0.0}\right]}}, \: \right. \ \ \displaystyle \left.{objVal = -{1600.0}}, \:{\hbox{\axiomType{Basis}\ } ={\left[ 2, \: 4, \: 1 \right]}}\right]$

(28)

Type: Record(X: Vector(Float),objVal: Float,Basis: List(Integer))

fricas

testEquals("floatNull(r3lu.X-X3)", "true")

Type: Void

fricas

testEquals("abs(r3lu.objVal-objVal3)<eps", "true")

Type: Void

fricas

testEquals("r3lu.Basis", "Basis3")

Type: Void

fricas

--
A4 := matrix [[1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0],_
              [0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0],_
              [0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0],_
              [0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0],_
              [3, 0, 6, 0, 5, 0, 7, 0, 1, 0, 0, 0, 0, 0, 1, 0],_
              [0, 2, 0, 4, 0, 10, 0, 4, 0, 1, 0, 0, 0, 0, 0, 1]]

$\label{eq29}\left[ \begin{array}{cccccccccccccccc} 1 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 \ 0 & 0 & 1 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 \ 0 & 0 & 0 & 0 & 1 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 \ 0 & 0 & 0 & 0 & 0 & 0 & 1 & 1 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 \ 3 & 0 & 6 & 0 & 5 & 0 & 7 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 1 & 0 \ 0 & 2 & 0 & 4 & 0 &{10}& 0 & 4 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 1$

(29)

Type: Matrix(NonNegativeInteger?)

fricas

b4 := vector [1, 1, 1, 1, 13, 10]

$\label{eq30}\left[ 1, \: 1, \: 1, \: 1, \:{13}, \:{10}\right]$

(30)

Type: Vector(PositiveInteger?)

fricas

c4 := vector [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1]

$\label{eq31}\left[ 0, \: 0, \: 0, \: 0, \: 0, \: 0, \: 0, \: 0, \: 0, \: 0, \: 1, \: 1, \: 1, \: 1, \: 1, \: 1 \right]$

(31)

Type: Vector(NonNegativeInteger?)

fricas

B4 := [11, 12, 13, 14, 15, 16]

$\label{eq32}\left[{11}, \:{12}, \:{13}, \:{14}, \:{15}, \:{16}\right]$

(32)

Type: List(PositiveInteger?)

fricas

X4:= [1.0, 0.0, 0.25, 0.7500000000_0000000001, 0.3, 0.7, 1.0, 0.0, 0.0, 0.0,
      0.0, 0.0, 0.0, 0.0, 0.0, 0.0]

$\label{eq33}\begin{array}{@{}l} \displaystyle \left[{1.0}, \:{0.0}, \:{0.25}, \:{0.7500000000 \_ 0000000001}, \:{0.3}, \:{0.7}, \:{1.0}, \:{0.0}, \:{0.0}, \right. \ \ \displaystyle \left.\:{0.0}, \:{0.0}, \:{0.0}, \:{0.0}, \:{0.0}, \:{0.0}, \:{0.0}\right]$

(33)

Type: List(Float)

fricas

objVal4:= 0.0

$\label{eq34}0.0$

(34)

Type: Float

fricas

Basis4:= [1,3,6,5,7,4]

$\label{eq35}\left[ 1, \: 3, \: 6, \: 5, \: 7, \: 4 \right]$

(35)

Type: List(PositiveInteger?)

fricas

r4 := revisedSimplex( A4, b4, c4, B4)

$\label{eq36}\begin{array}{@{}l} \displaystyle \left[{ \begin{array}{@{}l} \displaystyle X ={ \begin{array}{@{}l} \displaystyle \left[{1.0}, \:{0.0}, \:{0.25}, \:{0.7500000000 \_ 0000000001}, \:{0.3}, \:{0.7}, \:{1.0}, \: \right. \ \ \displaystyle \left.{0.0}, \:{0.0}, \:{0.0}, \:{0.0}, \:{0.0}, \:{0.0}, \:{0.0}, \:{0.0}, \:{0.0}\right]$

(36)

Type: Record(X: Vector(Float),objVal: Float,Basis: List(Integer))

fricas

testEquals("floatNull(r4.X-X4)", "true")

Type: Void

fricas

testEquals("abs(r4.objVal-objVal4)<eps", "true")

Type: Void

fricas

testEquals("r4.Basis", "Basis4")

Type: Void

fricas

r4lu := revisedSimplexLU( A4, b4, c4, B4)

$\label{eq37}\begin{array}{@{}l} \displaystyle \left[{ \begin{array}{@{}l} \displaystyle X ={ \begin{array}{@{}l} \displaystyle \left[{1.0}, \:{0.0}, \:{0.25}, \:{0.75}, \:{0.3}, \:{0.7}, \:{1.0}, \:{0.0}, \:{0.0}, \:{0.0}, \:{0.0}, \:{0.0}, \:{0.0}, \right. \ \ \displaystyle \left.\:{0.0}, \:{0.0}, \:{0.0}\right]$

(37)

Type: Record(X: Vector(Float),objVal: Float,Basis: List(Integer))

fricas

testEquals("floatNull(r4lu.X-X4)", "true")

Type: Void

fricas

testEquals("abs(r4lu.objVal-objVal4)<eps", "true")

Type: Void

fricas

testEquals("r4lu.Basis", "Basis4")

Type: Void

fricas

--
A5 := matrix [[1, -1, 1, 0, 0], [4, 9, 0, 1, 0], [-2, 4, 0, 0, 1]]

$\label{eq38}\left[ \begin{array}{ccccc} 1 & - 1 & 1 & 0 & 0 \ 4 & 9 & 0 & 1 & 0 \ - 2 & 4 & 0 & 0 & 1$

(38)

Type: Matrix(Integer)

fricas

c5 := vector [-1, -1, 0, 0, 0]

$\label{eq39}\left[ - 1, \: - 1, \: 0, \: 0, \: 0 \right]$

(39)

Type: Vector(Integer)

fricas

b5 := vector [2, 18, 4]

$\label{eq40}\left[ 2, \:{18}, \: 4 \right]$

(40)

Type: Vector(PositiveInteger?)

fricas

B5 := vector [3, 4, 5]

$\label{eq41}\left[ 3, \: 4, \: 5 \right]$

(41)

Type: Vector(PositiveInteger?)

fricas

X5 := [2.7692307692_307692308, 0.7692307692_3076923077, 0.0, 0.0,
       6.4615384615_384615385]

$\label{eq42}\begin{array}{@{}l} \displaystyle \left[{2.7692307692 \ 307692308}, \:{0.7692307692 \ 3076923 077}, \:{0.0}, \: \right. \ \ \displaystyle \left.{0.0}, \:{6.4615384615 \_ 384615385}\right]$

(42)

Type: List(Float)

fricas

objVal5:= - 3.5384615384_615384615

$\label{eq43}-{3.5384615384 \ 615384615}$

(43)

Type: Float

fricas

Basis5:= [1,2,5]

$\label{eq44}\left[ 1, \: 2, \: 5 \right]$

(44)

Type: List(PositiveInteger?)

fricas

r5 := revisedSimplex( A5, b5, c5, B5)

$\label{eq45}\begin{array}{@{}l} \displaystyle \left[{ \begin{array}{@{}l} \displaystyle X ={ \begin{array}{@{}l} \displaystyle \left[{2.7692307692 \ 307692308}, \:{0.7692307692 \ 3076923 077}, \: \right. \ \ \displaystyle \left.{0.0}, \:{0.0}, \:{6.4615384615 \_ 384615385}\right]$

(45)

Type: Record(X: Vector(Float),objVal: Float,Basis: List(Integer))

fricas

testEquals("floatNull(r5.X-X5)", "true")

Type: Void

fricas

testEquals("abs(r5.objVal-objVal5)<eps", "true")

Type: Void

fricas

testEquals("r5.Basis", "Basis5")

Type: Void

fricas

r5lu := revisedSimplexLU( A5, b5, c5, B5)

$\label{eq46}\begin{array}{@{}l} \displaystyle \left[{ \begin{array}{@{}l} \displaystyle X ={ \begin{array}{@{}l} \displaystyle \left[{2.7692307692 \ 307692308}, \:{0.7692307692 \ 3076923 077}, \: \right. \ \ \displaystyle \left.{0.0}, \:{0.0}, \:{6.4615384615 \_ 384615385}\right]$

(46)

Type: Record(X: Vector(Float),objVal: Float,Basis: List(Integer))

fricas

testEquals("floatNull(r5lu.X-X5)", "true")

Type: Void

fricas

testEquals("abs(r5lu.objVal-objVal5)<eps", "true")

Type: Void

fricas

testEquals("r5lu.Basis", "Basis5")

Type: Void

fricas

-- Results/Statistics

fricas

)set output algebra on

fricas

)version

Value = "FriCAS 1.3.7 compiled at Wed Jun 30 16:44:06 UTC 2021"

fricas

)lisp (lisp-implementation-type)

Value = "SBCL"

fricas

)lisp (lisp-implementation-version)

Value = "1.1.1"

statistics()

   =============================================================================
   General WARNINGS:
   * do not use ')clear completely' before having used 'statistics()'
     It clears the statistics without warning!
   * do not forget to pass the arguments of the testXxxx functions as Strings!
     Otherwise, the test will fail and statistics() will not notice!
   * testLibraryError does not prevent FriCAS from aborting the current block.
     Thus, if a block contains other test functions, they will not be executed
     and statistics() will not notice!

   =============================================================================
   Testsuite: Package: LinearProgramming
     failed (total): 0 (1)

   =============================================================================
   testsuite | testcases: failed (total) | tests: failed (total)
   Package: LinearProgramming    0     (1)               0    (30)
   =============================================================================
   File summary.
   unexpected failures: 0
   expected failures: 0
   unexpected passes: 0
   total tests: 30

Type: Void