The pure virtual function _nnz() must be defined by the used LP-solver and return the number of nonzero elements of the constraint matrix not including the right hand side and the bounds of the variables. The pure virtual function _nCol() must be defined by the used LP-solver and return the number of columns. The pure virtual function _maxRow() must be defined by the used LP-solver and return the maximal number of rows. The pure virtual function _maxCol() must be defined by the the used LP-solver and return the maximal number of columns. The pure virtual function _lpVarStat() must be defined by the used LP-solver and should return the status of the variable i in the LP-solution. This pure virtual function should load a basis into the LP-solver. _loadBasis ( Array & lpVarStat, Array & slackStat)=0 The pure virtual function _lBound() must be defined by the used LP-solver and return the lower bound of variable i. The pure virtual function _initialize() must be defined by the used LP-solver and should initialize the LP-solver with. _initialize ( OptSense sense, int nRow, int maxRow, int nCol, int maxCol, Array & obj, Array & lBound, Array & uBound, Array &rows)=0 The function getSimplexIterationLimit() retrieves the value of the iteration limit of the simplex algorithm. _getSimplexIterationLimit (int &limit) const =0 The pure virtual function _getInfeas() must be defined by the used LP-solver and can be called if the last linear program has been solved with the dual simplex method and is infeasible. _getInfeas (int &infeasRow, int &infeasCol, double *bInvRow) const =0 The pure virtual function _dualSimplex() must be defined by the used LP-solver and should call the dual simplex method of the used LP-solver. The pure virtual function _colRealloc() must be defined by the used LP-solver and should reallocate its memory such that up to newSize columns can be handled. The pure virtual function _changeLBound() must be defined by the used LP-solver and should set the upper bound of variable i to newUb. The pure virtual function _changeRhs() must be defined by the used LP-solver and should set the right hand side of the constraint matrix of the LP to newRhs. The pure virtual function _changeLBound() must be defined by the used LP-solver and should set the lower bound of variable i to newLb. The pure virtual function _barrier() must be defined by the used LP-solver and should call the barrier method of the used LP-solver. The pure virtual function _approx() must be defined by the used LP-solver and should call the approximative method of the used LP-solver. The pure virtual function _addRows() must be defined by the used LP-solver and should add the rows given in the buffer newRows to the LP. The pure virtual function _addCols() must be defined by the used LP-solver and should add the columns newCols to the LP. Public Member Functions inherited from abacus::AbacusRoot Writes the complete basis of an optimal linear program to a file. More.Ĭhanges the iteration limit of the Simplex algorithm. Performs a reallocation of the row space of the linear program. Pivots the slack variables stored in the buffer rows into the basis. PivotSlackVariableIn ( ArrayBuffer &rows) Performs the optimization of the linear program. Loads a new basis for the linear program. LoadBasis ( Array & lpVarStat, Array & slackStat) This version of the function initialize() performs like its previous version, but also initializes the basis with the arguments: More. Initialize ( OptSense sense, int nRow, int maxRow, int nCol, int maxCol, Array & obj, Array & lBound, Array & uBound, Array &rows, Array & lpVarStat, Array & slackStat) Loads the linear program defined by its arguments. Initialize ( OptSense sense, int nRow, int maxRow, int nCol, int maxCol, Array & obj, Array & lBound, Array & uBound, Array &rows) GetSimplexIterationLimit (int &limit) const GetInfeas (int &infeasRow, int &infeasCol, double *bInvRow) constĬan be called if the last linear program has been solved with the dual simplex method and is infeasible and all inactive variables price out correctly. Performs a reallocation of the column space of the linear program. More.Ĭhanges the upper bound of a single column. More.Ĭhanges the complete right hand side of the linear program. More.Ĭhanges the lower bound of a single column. More.ĭescribes if parts of the solution like x-values, reduced costs, etc. The optimization status of the linear program. The solution method for the linear program.
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