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LP-Simplex 2 Phasen Algorithmus minimize_lp

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(15) \text\small\blue{LP minimization \mathbb{LP_{min}} works analogously to LP maximization, but\\ in the opposite direction of the gradient. This results in the following changes:\\ \underline{Optimality test}: All coefficients of the objective function \mathbb{Z}_{min} ≤ 0\\ \underline{Pivot column}: largest entry in \mathbb{Z_{min}} } (18) \text\small\blue{As in Max-LP, set the slack variable to -1 for NB equal to or greater than.\\ For equations, remove the slack variable \to 0\\ Phase 1:\\Search for a feasible basic solution using the simplex algorithm and an auxiliary objective function.\\ Block entry after slack variables and before b variables } (21) \text\small\blue{Setting up the initial simplex table. In each row where we subtract a slack variable, we additionally add an auxiliary variable.} (23) \text\small\blue{Replacing the objective function Z with the column sum of all auxiliary variables \to Z'} (25) \text\small\blue{By adding all lines containing an auxiliary variable to the target function line, we set all entries of the auxiliary variables in the target function line to zero: Z'=Load(Start)+Z'\times Start\\ Pivot selection is made manually based on the quotient Qb2 \to b/pivot column.} (35) \text\small\blue{The initial problem now has a basic solution.\\ Remove the data from the auxiliary variables.\\ In the second phase, the optimal target value is determined using the simplex table.} (37) \text\small\blue{Protocol for basis change \{base columns\},\{row pivot, column pivot\}\\ The pivot \{z,s\} describes a basis change \\ \to Column s enters the basis, column z leaves the basis. \\ \to Transform Z, Z is expressed by basis variables x1 and x2\\ \to A_2 receives the new Z = Z+A_1(1)Z(1)+A_1(2)Z(2)}:\ ("\text\small\blue{https://statmath.wu.ac.at/~leydold/MOK/HTML/node164.html}") Example x1,x2,x3,x4 https://www.mikrocontroller.net/attachment/156858/SimplexMeFile_2012-10-08_19-55.pdf Phase1: A_{11}...A_{18} A_1 "\text\small\blue{Protokoll der Basiswechsel \{Basisspalten\},\{ZeilenPivot,Spaltenpivot\}\\Der Pivot \{z1,s1\} beschreibt einen Basiwechsel \to Spalte s1 geht in die Basis, Spalte z1 verlässt die Basis. \\Der zweite Basiswechsel \{7,1\} löscht den Basiseintrag\\Damit bleibt in Zeile 6/Spalte 4 nur x4 in der Phase2 Basis \to A_2 erhält die neue Z = Z+A_1(6)Z(4)}:\\" BasisPhase2:={{5, 8, 7, 10, 9, 4, 0}, {2, 8}, {5, 12, 7, 10, 9, 4, 0}, {7, 1}, {5, 12, 7, 10, 9, 4, 3}, {4, 10}, {5, 12, 7, 10, 9, 4, 3}, {4, 10}, {5, 12, 7, 13, 9, 4, 3}, {6, 4}, {5, 12, 7, 13, 9, 4, 3}, {6, 4}, {5, 12, 7, 13, 9, 2, 3}, {35, 36}, {6, 2}, {5, 12, 7, 13, 9, 14, 1}, {7, 1}} {Basiswechsel}, {Pivot}-Folge abarbeiten von rechts nach links.
https://sagecell.sagemath.org/?q=bxgkkw https://sagecell.sagemath.org/?q=ohjkyg/td]
 Matrix Functions
Die Ausstattung zur Matrizen-Behandlung ist sehr schwach ausgeprägt. Es gibt keine Spalten-Werkzeuge. Um Spalten zu bearbeiten muss die Matrix transponiert werden: Element() Take() First() Last() können dann Zeilen barbeiten die mit Join() Append() wieder zusammen gebaut werden. Die bearbeiteten Zeilen werden nach einer Rück-Transponierung wieder zu Spalten"The features for matrix processing are very limited. There are no column tools. To edit columns, the matrix must be transposed: Element() Take() First() Last() can then edit rows that are reassembled with Join() Append(). After transposing back, the edited rows become columns again.