' DotNumerics Simplex Extender ' Copyright 2015 Gregor Reichert, Daniel Wagner O. de Medeiros ' ' This file is part of DWSIM. ' ' DWSIM is free software: you can redistribute it and/or modify ' it under the terms of the GNU General Public License as published by ' the Free Software Foundation, either version 3 of the License, or ' (at your option) any later version. ' ' DWSIM is distributed in the hope that it will be useful, ' but WITHOUT ANY WARRANTY; without even the implied warranty of ' MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the ' GNU General Public License for more details. ' ' You should have received a copy of the GNU General Public License ' along with DWSIM. If not, see . Imports DotNumerics.Optimization Public Module SimplexExtender Public Delegate Function ObjectiveFunction(ByVal x() As Double) As Double ''' ''' Simplified implementation of Nelder-Mead-Simplex-Downhill algorithm. No "Reduction" and no "Expansion" implemented yet. ''' https://en.wikipedia.org/wiki/Nelder%E2%80%93Mead_method ''' ''' simplex solver instance ''' objective function delegate ''' optimization variables ''' the values of the variables that minimize the objective function value ''' Public Function ComputeMin2(simplexsolver As Simplex, objfunc As ObjectiveFunction, ByVal Var() As OptBoundVariable) As Double() Dim cnt As Integer = 0 Dim i, k, IdxMax As Integer Dim Dx, FVnew, LF, LF1 As Double Dim Beta As Double = 0.5 'Dimension 0: point number 'Dimension 1: coordinates of points; last column = 1 is indicating "at limiting border" Dim Points(Var.Length, Var.Length - 1) As Double Dim FuncVal(Var.Length) As Double Dim Pt(Var.Length - 1) As Double Dim CenterPt(Var.Length - 1) As Double 'Calculate initial value For i = 0 To Var.Length - 1 'Pt(i) = (Var(i).UpperBound - Var(i).LowerBound) / 2 'Pt(i) = 0 Pt(i) = Var(i).InitialGuess Next 'Initialise points For k = 0 To Var.Length 'points For i = 0 To Var.Length - 1 'coordinates Points(k, i) = Pt(i) Next Next For k = 1 To Var.Length Dx = (Var(k - 1).UpperBound - Var(k - 1).LowerBound) / 10 Points(k, k - 1) += Dx Next 'Calculate point values For k = 0 To Var.Length For i = 0 To Var.Length - 1 Pt(i) = Points(k, i) Next FuncVal(k) = objfunc(Pt) Next Do cnt += 1 'Search worst value e.g. maximum Gibbs Enthalpy IdxMax = 0 For k = 1 To Var.Length If FuncVal(k) > FuncVal(IdxMax) Then IdxMax = k Next 'Calculate center point as average from all points except max For i = 0 To Var.Length - 1 CenterPt(i) = 0 Next For k = 0 To Var.Length If k <> IdxMax Then For i = 0 To Var.Length - 1 CenterPt(i) += Points(k, i) / Var.Length Next End If Next 'reflect worst point at center point LF = 1 For i = 0 To Var.Length - 1 LF1 = 1 Pt(i) = CenterPt(i) + CenterPt(i) - Points(IdxMax, i) 'Check if point is inside bounds If Pt(i) < Var(i).LowerBound Then LF1 = (Var(i).LowerBound - CenterPt(i)) / (Points(IdxMax, i) - CenterPt(i)) End If If LF1 < LF Then LF = LF1 If Pt(i) > Var(i).UpperBound Then LF1 = (Var(i).UpperBound - CenterPt(i)) / (Points(IdxMax, i) - CenterPt(i)) End If If LF1 < LF Then LF = -LF1 Next If LF < 1 Then For i = 0 To Var.Length - 1 Pt(i) = CenterPt(i) + LF * (CenterPt(i) - Points(IdxMax, i)) Next End If FVnew = objfunc(Pt) If FVnew < FuncVal(IdxMax) Then 'replace worst point by new one FuncVal(IdxMax) = FVnew For i = 0 To Var.Length - 1 Points(IdxMax, i) = Pt(i) Next Else 'contract worst point to center point For i = 0 To Var.Length - 1 Pt(i) = 0.5 * CenterPt(i) + 0.5 * Points(IdxMax, i) Next FVnew = objfunc(Pt) 'check if solution is not improving anymore If FVnew > FuncVal(IdxMax) - simplexsolver.Tolerance Or cnt > simplexsolver.MaxFunEvaluations Then Exit Do 'and replace worst value by contracted value FuncVal(IdxMax) = FVnew For i = 0 To Var.Length - 1 Points(IdxMax, i) = Pt(i) Next End If Loop 'Search best value to be returned e.g. minimum Gibbs Enthalpy IdxMax = 0 For k = 1 To Var.Length If FuncVal(k) < FuncVal(IdxMax) Then IdxMax = k Next For i = 0 To Var.Length - 1 Pt(i) = Points(IdxMax, i) Next Return Pt End Function End Module