XPRSprob Methods

Add AfterObjective callback.

Add AfterObjective callback with the specified priority.

Add AfterObjective callback with a user object that is passed to the callback on invocation.

Add AfterObjective callback with specified priority and a user object that is passed to the callback on invocation.

Add BarIteration callback.

Add BarIteration callback with the specified priority.

Add BarIteration callback with a user object that is passed to the callback on invocation.

Add BarIteration callback with specified priority and a user object that is passed to the callback on invocation.

Add Barlog callback.

Add Barlog callback with the specified priority.

Add Barlog callback with a user object that is passed to the callback on invocation.

Add Barlog callback with specified priority and a user object that is passed to the callback on invocation.

Add BeforeObjective callback.

Add BeforeObjective callback with the specified priority.

Add BeforeObjective callback with a user object that is passed to the callback on invocation.

Add BeforeObjective callback with specified priority and a user object that is passed to the callback on invocation.

Add BeforeSolve callback.

Add BeforeSolve callback with the specified priority.

Add BeforeSolve callback with a user object that is passed to the callback on invocation.

Add BeforeSolve callback with specified priority and a user object that is passed to the callback on invocation.

Add ChangeBranchObject callback.

Add ChangeBranchObject callback with the specified priority.

Add ChangeBranchObject callback with a user object that is passed to the callback on invocation.

Add ChangeBranchObject callback with specified priority and a user object that is passed to the callback on invocation.

Add CheckTime callback.

Add CheckTime callback with the specified priority.

Add CheckTime callback with a user object that is passed to the callback on invocation.

Add CheckTime callback with specified priority and a user object that is passed to the callback on invocation.

Add Chgbranch callback.

Add Chgbranch callback with the specified priority.

Add Chgbranch callback with a user object that is passed to the callback on invocation.

Add Chgbranch callback with specified priority and a user object that is passed to the callback on invocation.

Add Chgnode callback.

Add Chgnode callback with the specified priority.

Add Chgnode callback with a user object that is passed to the callback on invocation.

Add Chgnode callback with specified priority and a user object that is passed to the callback on invocation.

Allows columns to be added to the matrix after passing it to the Optimizer using the input routines.

Allows columns to be added to the matrix after passing it to the Optimizer using the input routines.

Add ComputeRestart callback.

Add ComputeRestart callback with the specified priority.

Add ComputeRestart callback with a user object that is passed to the callback on invocation.

Add ComputeRestart callback with specified priority and a user object that is passed to the callback on invocation.

Add Cutlog callback.

Add Cutlog callback with the specified priority.

Add Cutlog callback with a user object that is passed to the callback on invocation.

Add Cutlog callback with specified priority and a user object that is passed to the callback on invocation.

Add Cutmgr callback.

Add Cutmgr callback with the specified priority.

Add Cutmgr callback with a user object that is passed to the callback on invocation.

Add Cutmgr callback with specified priority and a user object that is passed to the callback on invocation.

Adds cuts directly to the matrix at the current node. Any cuts added to the matrix at the current node and not deleted at the current node will be automatically added to the cut pool. The cuts added to the cut pool will be automatically restored at descendant nodes.

Adds cuts directly to the matrix at the current node. Any cuts added to the matrix at the current node and not deleted at the current node will be automatically added to the cut pool. The cuts added to the cut pool will be automatically restored at descendant nodes.

Add Estimate callback.

Add Estimate callback with the specified priority.

Add Estimate callback with a user object that is passed to the callback on invocation.

Add Estimate callback with specified priority and a user object that is passed to the callback on invocation.

Add GapNotify callback.

Add GapNotify callback with the specified priority.

Add GapNotify callback with a user object that is passed to the callback on invocation.

Add GapNotify callback with specified priority and a user object that is passed to the callback on invocation.

Adds one or more general constraints to the problem. Each general constraint y = f(x1, ..., xn, c1, ..., cn) consists of one or more (input) columns xi, zero or more constant values ci and a resultant (output column) y, different from all xi. General constraints include maximum and minimum (arbitrary number of input columns of any type and arbitrary number of input values, at least one total), and and or (at least one binary input column, no constant values, binary resultant) and absolute value (exactly one input column of arbitrary type, no constant values).

Adds one or more general constraints to the problem. Each general constraint y = f(x1, ..., xn, c1, ..., cn) consists of one or more (input) columns xi, zero or more constant values ci and a resultant (output column) y, different from all xi. General constraints include maximum and minimum (arbitrary number of input columns of any type and arbitrary number of input values, at least one total), and and or (at least one binary input column, no constant values, binary resultant) and absolute value (exactly one input column of arbitrary type, no constant values).

Add Infnode callback.

Add Infnode callback with the specified priority.

Add Infnode callback with a user object that is passed to the callback on invocation.

Add Infnode callback with specified priority and a user object that is passed to the callback on invocation.

Add Intsol callback.

Add Intsol callback with the specified priority.

Add Intsol callback with a user object that is passed to the callback on invocation.

Add Intsol callback with specified priority and a user object that is passed to the callback on invocation.

Add Lplog callback.

Add Lplog callback with the specified priority.

Add Lplog callback with a user object that is passed to the callback on invocation.

Add Lplog callback with specified priority and a user object that is passed to the callback on invocation.

Add Message callback.

Add Message callback with the specified priority.

Add Message callback with a user object that is passed to the callback on invocation.

Add Message callback with specified priority and a user object that is passed to the callback on invocation.

Add Miplog callback.

Add Miplog callback with the specified priority.

Add Miplog callback with a user object that is passed to the callback on invocation.

Add Miplog callback with specified priority and a user object that is passed to the callback on invocation.

Adds a new feasible, infeasible or partial MIP solution for the problem to the Optimizer.

Add MipThread callback.

Add MipThread callback with the specified priority.

Add MipThread callback with a user object that is passed to the callback on invocation.

Add MipThread callback with specified priority and a user object that is passed to the callback on invocation.

Add MipThreadDestroy callback.

Add MipThreadDestroy callback with the specified priority.

Add MipThreadDestroy callback with a user object that is passed to the callback on invocation.

Add MipThreadDestroy callback with specified priority and a user object that is passed to the callback on invocation.

Add MsgHandler callback.

Add MsgHandler callback with the specified priority.

Add MsgHandler callback with a user object that is passed to the callback on invocation.

Add MsgHandler callback with specified priority and a user object that is passed to the callback on invocation.

Add MsJobEnd callback.

Add MsJobEnd callback with the specified priority.

Add MsJobEnd callback with a user object that is passed to the callback on invocation.

Add MsJobEnd callback with specified priority and a user object that is passed to the callback on invocation.

Add MsJobStart callback.

Add MsJobStart callback with the specified priority.

Add MsJobStart callback with a user object that is passed to the callback on invocation.

Add MsJobStart callback with specified priority and a user object that is passed to the callback on invocation.

Add MsWinner callback.

Add MsWinner callback with the specified priority.

Add MsWinner callback with a user object that is passed to the callback on invocation.

Add MsWinner callback with specified priority and a user object that is passed to the callback on invocation.

Add Newnode callback.

Add Newnode callback with the specified priority.

Add Newnode callback with a user object that is passed to the callback on invocation.

Add Newnode callback with specified priority and a user object that is passed to the callback on invocation.

Add NlpCoefEvalError callback.

Add NlpCoefEvalError callback with the specified priority.

Add NlpCoefEvalError callback with a user object that is passed to the callback on invocation.

Add NlpCoefEvalError callback with specified priority and a user object that is passed to the callback on invocation.

Add Nodecutoff callback.

Add Nodecutoff callback with the specified priority.

Add Nodecutoff callback with a user object that is passed to the callback on invocation.

Add Nodecutoff callback with specified priority and a user object that is passed to the callback on invocation.

Add NodeLPSolved callback.

Add NodeLPSolved callback with the specified priority.

Add NodeLPSolved callback with a user object that is passed to the callback on invocation.

Add NodeLPSolved callback with specified priority and a user object that is passed to the callback on invocation.

Appends an objective function with the given coefficients to a multi-objective problem. The weight and priority of the objective are set to the given values.

Add Optnode callback.

Add Optnode callback with the specified priority.

Add Optnode callback with a user object that is passed to the callback on invocation.

Add Optnode callback with specified priority and a user object that is passed to the callback on invocation.

Add PreIntsol callback.

Add PreIntsol callback with the specified priority.

Add PreIntsol callback with a user object that is passed to the callback on invocation.

Add PreIntsol callback with specified priority and a user object that is passed to the callback on invocation.

Add Prenode callback.

Add Prenode callback with the specified priority.

Add Prenode callback with a user object that is passed to the callback on invocation.

Add Prenode callback with specified priority and a user object that is passed to the callback on invocation.

Add Presolve callback.

Add Presolve callback with the specified priority.

Add Presolve callback with a user object that is passed to the callback on invocation.

Add Presolve callback with specified priority and a user object that is passed to the callback on invocation.

Adds one or more piecewise linear constraints to the problem. Each piecewise linear constraint y = f(x) consists of an (input) column x, a (different) resultant (output column) y and a piecewise linear function f. The piecewise linear function f is described by at least two breakpoints, which are given as combinations of x- and y-values. Discontinuous piecewise linear functions are supported, in this case both the left and right limit at a given point need to be entered as breakpoints. To differentiate between left and right limit, the breakpoints need to be given as a list with non-decreasing x-values.

Adds one or more piecewise linear constraints to the problem. Each piecewise linear constraint y = f(x) consists of an (input) column x, a (different) resultant (output column) y and a piecewise linear function f. The piecewise linear function f is described by at least two breakpoints, which are given as combinations of x- and y-values. Discontinuous piecewise linear functions are supported, in this case both the left and right limit at a given point need to be entered as breakpoints. To differentiate between left and right limit, the breakpoints need to be given as a list with non-decreasing x-values.

Adds a new quadratic matrix into a row defined by triplets.

Adds a new quadratic matrix into a row defined by triplets.

Allows rows to be added to the matrix after passing it to the Optimizer using the input routines.

Allows rows to be added to the matrix after passing it to the Optimizer using the input routines.

Allows rows to be added to the matrix after passing it to the Optimizer using the input routines.

Allows rows to be added to the matrix after passing it to the Optimizer using the input routines.

Add Sepnode callback.

Add Sepnode callback with the specified priority.

Add Sepnode callback with a user object that is passed to the callback on invocation.

Add Sepnode callback with specified priority and a user object that is passed to the callback on invocation.

Allows sets to be added to the problem after passing it to the Optimizer using the input routines.

Allows sets to be added to the problem after passing it to the Optimizer using the input routines.

Add SlpCascadeEnd callback.

Add SlpCascadeEnd callback with the specified priority.

Add SlpCascadeEnd callback with a user object that is passed to the callback on invocation.

Add SlpCascadeEnd callback with specified priority and a user object that is passed to the callback on invocation.

Add SlpCascadeStart callback.

Add SlpCascadeStart callback with the specified priority.

Add SlpCascadeStart callback with a user object that is passed to the callback on invocation.

Add SlpCascadeStart callback with specified priority and a user object that is passed to the callback on invocation.

Add SlpCascadeVar callback.

Add SlpCascadeVar callback with the specified priority.

Add SlpCascadeVar callback with a user object that is passed to the callback on invocation.

Add SlpCascadeVar callback with specified priority and a user object that is passed to the callback on invocation.

Add SlpCascadeVarFail callback.

Add SlpCascadeVarFail callback with the specified priority.

Add SlpCascadeVarFail callback with a user object that is passed to the callback on invocation.

Add SlpCascadeVarFail callback with specified priority and a user object that is passed to the callback on invocation.

Add SlpConstruct callback.

Add SlpConstruct callback with the specified priority.

Add SlpConstruct callback with a user object that is passed to the callback on invocation.

Add SlpConstruct callback with specified priority and a user object that is passed to the callback on invocation.

Add SlpDrCol callback.

Add SlpDrCol callback with the specified priority.

Add SlpDrCol callback with a user object that is passed to the callback on invocation.

Add SlpDrCol callback with specified priority and a user object that is passed to the callback on invocation.

Add SlpIntSol callback.

Add SlpIntSol callback with the specified priority.

Add SlpIntSol callback with a user object that is passed to the callback on invocation.

Add SlpIntSol callback with specified priority and a user object that is passed to the callback on invocation.

Add SlpIterEnd callback.

Add SlpIterEnd callback with the specified priority.

Add SlpIterEnd callback with a user object that is passed to the callback on invocation.

Add SlpIterEnd callback with specified priority and a user object that is passed to the callback on invocation.

Add SlpIterStart callback.

Add SlpIterStart callback with the specified priority.

Add SlpIterStart callback with a user object that is passed to the callback on invocation.

Add SlpIterStart callback with specified priority and a user object that is passed to the callback on invocation.

Add SlpIterVar callback.

Add SlpIterVar callback with the specified priority.

Add SlpIterVar callback with a user object that is passed to the callback on invocation.

Add SlpIterVar callback with specified priority and a user object that is passed to the callback on invocation.

Add SlpPreUpdateLinearization callback.

Add SlpPreUpdateLinearization callback with the specified priority.

Add SlpPreUpdateLinearization callback with a user object that is passed to the callback on invocation.

Add SlpPreUpdateLinearization callback with specified priority and a user object that is passed to the callback on invocation.

Add UserSolNotify callback.

Add UserSolNotify callback with the specified priority.

Add UserSolNotify callback with a user object that is passed to the callback on invocation.

Add UserSolNotify callback with specified priority and a user object that is passed to the callback on invocation.

Alters or changes matrix elements, right hand sides and constraint senses in the current problem.

Calculates the condition number of the current basis after solving the LP relaxation. *@deprecated

Calculates various measures for the stability of the current basis, including the basis condition number.

Returns upper and lower sensitivity ranges for specified variables' lower and upper bounds. If the bounds are varied within these ranges the current basis remains optimal and feasible.

Post-multiplies a (row) vector provided by the user by the inverse of the current basis.

Calculates the objective value of a given solution.

Calculates the objective value of the given objective function in a multi-objective problem.

Calculates the reduced cost values for a given (row) dual solution.

Calculates the row slack values for a given solution.

Calculates the required property of a solution, like maximum infeasibility of a given primal and dual solution.

Used to change the bounds on columns in the matrix.

Used to change a single coefficient in the matrix. If the coefficient does not already exist, a new coefficient will be added to the matrix. If many coefficients are being added to a row of the matrix, it may be more efficient to delete the old row of the matrix and add a new row.

Convenience wrapper for ChgColType(int, int[], char[]).

Convenience wrapper for ChgGlbLimit(int, int[], double[]).

Used to change semi-continuous or semi-integer lower bounds, or upper limits on partial integers.

Used to change multiple coefficients in the matrix. If any coefficient does not already exist, it will be added to the matrix. If many coefficients are being added to a row of the matrix, it may be more efficient to delete the old row of the matrix and add a new one.

Used to change multiple coefficients in the matrix. If any coefficient does not already exist, it will be added to the matrix. If many coefficients are being added to a row of the matrix, it may be more efficient to delete the old row of the matrix and add a new one.

Used to change multiple quadratic coefficients in the objective function. If any of the coefficients does not exist already, new coefficients will be added to the objective function.

Used to change multiple quadratic coefficients in the objective function. If any of the coefficients does not exist already, new coefficients will be added to the objective function.

Convenience wrapper for ChgObj(int, int[], double[]).

Used to change the objective function coefficients.

Modifies one or more coefficients of an objective function in a multi-objective problem. If the objective already exists, any coefficients not present in the colind and objcoef arrays will unchanged. If the objective does not exist, it will be added to the problem.

Changes the problem's objective function sense to minimize or maximize.

Used to change a single quadratic coefficient in the objective function corresponding to the variable pair (objqcol1,objqcol2) of the Hessian matrix.

Changes a single quadratic coefficient in a row.

Convenience wrapper for ChgRHS(int, int[], double[]).

Used to change right—hand side values of the problem.

Convenience wrapper for ChgRHSRange(int, int[], double[]).

Used to change the range for a row of the problem matrix.

Convenience wrapper for ChgRowType(int, int[], char[]).

Used to change the type of a row in the matrix.

Resets the search for Irreducible Infeasible Sets (IIS).

Clears extra information attached to a range of rows.

Create a copy of the problem, including controls and callbacks.

Copy callbacks to this XPRSprob from another

Copies controls defined for one problem to another.

Provides a basic optimal solution for a given solution of an LP problem. This function behaves like the crossover after the barrier algorithm.

Delete columns from a matrix.

During the branch and bound search, cuts are stored in the cut pool to be applied at descendant nodes. These cuts may be removed from a given node using delCuts, but if this is to be applied in a large number of cases, it may be preferable to remove the cut completely from the cut pool. This is achieved using delCPCuts.

During the branch and bound search, cuts are stored in the cut pool to be applied at descendant nodes. These cuts may be removed from a given node using delCuts, but if this is to be applied in a large number of cases, it may be preferable to remove the cut completely from the cut pool. This is achieved using delCPCuts.

During the branch and bound search, cuts are stored in the cut pool to be applied at descendant nodes. These cuts may be removed from a given node using delCuts, but if this is to be applied in a large number of cases, it may be preferable to remove the cut completely from the cut pool. This is achieved using delCPCuts.

During the branch and bound search, cuts are stored in the cut pool to be applied at descendant nodes. These cuts may be removed from a given node using delCuts, but if this is to be applied in a large number of cases, it may be preferable to remove the cut completely from the cut pool. This is achieved using delCPCuts.

Deletes cuts from the matrix at the current node. Cuts from the parent node which have been automatically restored may be deleted as well as cuts added to the current node using addCuts or loadCuts. The cuts to be deleted can be specified in a number of ways. If a cut is ruled out by any one of the criteria it will not be deleted.

Deletes cuts from the matrix at the current node. Cuts from the parent node which have been automatically restored may be deleted as well as cuts added to the current node using addCuts or loadCuts. The cuts to be deleted can be specified in a number of ways. If a cut is ruled out by any one of the criteria it will not be deleted.

Deletes cuts from the matrix at the current node. Cuts from the parent node which have been automatically restored may be deleted as well as cuts added to the current node using addCuts or loadCuts. The cuts to be deleted can be specified in a number of ways. If a cut is ruled out by any one of the criteria it will not be deleted.

Deletes cuts from the matrix at the current node. Cuts from the parent node which have been automatically restored may be deleted as well as cuts added to the current node using addCuts or loadCuts. The cuts to be deleted can be specified in a number of ways. If a cut is ruled out by any one of the criteria it will not be deleted.

Deletes cuts from the matrix at the current node. Cuts from the parent node which have been automatically restored may be deleted as well as cuts added to the current node using addCuts or loadCuts. The cuts to be deleted can be specified in a number of ways. If a cut is ruled out by any one of the criteria it will not be deleted.

Delete general constraints from a problem.

Delete indicator constraints. This turns the specified rows into normal rows (not controlled by indicator variables).

Removes an objective function from a multi-objective problem. Any objectives with index > objidx will be shifted down. Deleting the last objective function in the problem causes all the objective coefficients to be zeroed, but OBJECTIVES remains set to 1.

Delete piecewise linear constraints from a problem.

Deletes the quadratic part of a row or of the objective function.

Delete rows from a matrix.

Delete sets from a problem.

Destroy the problem, freeing all native resources used. Equivalent to calling Dipose().

Displays the list of controls and their current value for those controls that have been set to a non default value.

Performs a dual side range sensitivity analysis, i.e. calculates estimates for the possible ranges for dual values.

Initiates a search for an Irreducible Infeasible Set (IIS) in an infeasible problem.

Initiates a search for an Irreducible Infeasible Set (IIS) in an infeasible problem.

Fixes all the MIP entities to the values of the last found MIP solution. This is useful for finding the reduced costs for the continuous variables after the integer variables have been fixed to their optimal values.

Pre-multiplies a (column) vector provided by the user by the inverse of the current matrix.

Accesses the id number and the type information of an attribute given its name. An attribute name may be for example XPRS_ROWS. Names are case-insensitive and may or may not have the XPRS_ prefix. The id number is the constant used to identify the attribute for calls to functions such as getIntAttrib. The type information returned will be one of the below integer constants defined in the xprs.h header file. The function will return an id number of 0 and a type value of XPRS_TYPE_NOTDEFINED if the name is not recognized as an attribute name. Note that this will occur if the name is a control name and not an attribute name.

Returns the current basis into the user's data arrays.

Returns the current basis status for a specific column or row.

Returns a single coefficient in the constraint matrix.

Returns a single coefficient in the constraint matrix.

Returns the nonzeros in the constraint matrix for the columns in a given range.

Returns the nonzeros in the constraint matrix for the columns in a given range.

Returns the nonzeros in the constraint matrix for the columns in a given range.

Returns the nonzeros in the constraint matrix for the columns in a given range.

Convenience wrapper for GetColType(char[], int, int).

Convenience wrapper for GetColType(char[], int, int).

Returns the column types for the columns in a given range.

Accesses the id number and the type information of a control given its name. A control name may be for example XPRS_PRESOLVE. Names are case-insensitive and may or may not have the XPRS_ prefix. The id number is the constant used to identify the control for calls to functions such as getIntControl. The function will return an id number of 0 and a type value of XPRS_TYPE_NOTDEFINED if the name is not recognized as a control name. Note that this will occur if the name is an attribute name and not a control name.

Returns a list of cut indices from the cut pool.

Returns a list of cut indices from the cut pool.

Returns a list of cut indices from the cut pool.

Returns cuts from the cut pool. A list of cut pointers in the array rowind must be passed to the routine. The columns and elements of the cut will be returned in the regions pointed to by the colind and cutcoef parameters. The columns and elements will be stored contiguously and the starting point of each cut will be returned in the region pointed to by the start parameter.

Returns cuts from the cut pool. A list of cut pointers in the array rowind must be passed to the routine. The columns and elements of the cut will be returned in the regions pointed to by the colind and cutcoef parameters. The columns and elements will be stored contiguously and the starting point of each cut will be returned in the region pointed to by the start parameter.

Retrieves a list of cut pointers for the cuts active at the current node.

Retrieves a list of cut pointers for the cuts active at the current node.

Retrieves a list of cut pointers for the cuts active at the current node.

Used to return in which rows a list of cuts are currently loaded into the Optimizer. This is useful for example to retrieve the duals associated with active cuts.

Used to calculate the slack value of a cut with respect to the current LP relaxation solution. The slack is calculated from the cut itself, and might be requested for any cut (even if it is not currently loaded into the problem).

Enables users to retrieve the values of various double problem attributes. Problem attributes are set during loading and optimization of a problem.

Enables users to retrieve the values of various double problem attributes. Problem attributes are set during loading and optimization of a problem.

Retrieves the value of a given double control parameter.

Retrieves the value of a given double control parameter.

Used to return the directives that have been loaded into a matrix. Priorities, forced branching directions and pseudo costs can be returned. If called after presolve, getDirs will get the directives for the presolved problem.

Used to return the directives that have been loaded into a matrix. Priorities, forced branching directions and pseudo costs can be returned. If called after presolve, getDirs will get the directives for the presolved problem.

Used to return the directives that have been loaded into a matrix. Priorities, forced branching directions and pseudo costs can be returned. If called after presolve, getDirs will get the directives for the presolved problem.

Retrieves a dual ray (dual unbounded direction) for the current problem, if the problem is found to be infeasible.

Used to obtain the dual values following optimization with optimize.

Returns the general constraints y = f(x1, ..., xn, c1, ..., cm) in a given range.

Returns the general constraints y = f(x1, ..., xn, c1, ..., cm) in a given range.

Returns information for an Irreducible Infeasible Set: size, variables and constraints (row and column vectors), and conflicting sides of the variables. For pure linear problems there is also information on duals, reduced costs and isolations.

Returns the index for a specified row or column name.

Returns the index for a specified row or column name.

Returns the indicator constraint condition (indicator variable and complement flag) associated to the rows in a given range.

Returns a list of infeasible primal and dual variables.

Enables users to recover the values of various integer problem attributes. Problem attributes are set during loading and optimization of a problem.

Enables users to recover the values of various integer problem attributes. Problem attributes are set during loading and optimization of a problem.

Enables users to recover the values of various integer control parameters

Enables users to recover the values of various integer control parameters

Get a solution.

Used to obtain the last barrier solution values following optimization that used the barrier solver.

Get the djs values of a solution.

Get the duals values of a solution.

Get the slack values of a solution.

Get the x values of a solution.

Returns the error message corresponding to the last error encountered by a library function.

Returns the error message corresponding to the last error encountered by a library function.

Convenience wrapper for GetLB(double[], int, int).

Convenience wrapper for GetLB(double[], int, int).

Returns the lower bounds for the columns in a given range.

Enables users to recover the values of various integer problem attributes. Problem attributes are set during loading and optimization of a problem.

Enables users to recover the values of various integer problem attributes. Problem attributes are set during loading and optimization of a problem.

Enables users to recover the values of various integer control parameters

Enables users to recover the values of various integer control parameters

Get a solution.

Used to obtain the LP solution values following optimization.

Used to obtain the LP solution values following optimization.

Get the djs values of a solution.

Get the duals values of a solution.

Get the slack values of a solution.

Used to obtain a single LP solution value following optimization.

Get the x values of a solution.

Retrieves the current suppression status of a message.

Retrieves the current suppression status of a message.

Retrieves integr and entity information about a problem. It must be called before mipOptimize if the presolve option is used.

Retrieves integr and entity information about a problem. It must be called before mipOptimize if the presolve option is used.

Retrieves integr and entity information about a problem. It must be called before mipOptimize if the presolve option is used.

Retrieves integr and entity information about a problem. It must be called before mipOptimize if the presolve option is used.

Get a solution.

Used to obtain the solution values of the last MIP solution that was found.

Used to obtain the solution values of the last MIP solution that was found.

Get the slack values of a solution.

Used to obtain a single solution value of the last MIP solution that was found.

Get the x values of a solution.

Returns the nonzeros in the quadratic objective coefficients matrix for the columns in a given range. To achieve maximum efficiency, getMQObj returns the lower triangular part of this matrix only.

Returns the nonzeros in the quadratic objective coefficients matrix for the columns in a given range. To achieve maximum efficiency, getMQObj returns the lower triangular part of this matrix only.

Returns the nonzeros in the quadratic objective coefficients matrix for the columns in a given range. To achieve maximum efficiency, getMQObj returns the lower triangular part of this matrix only.

Returns the nonzeros in the quadratic objective coefficients matrix for the columns in a given range. To achieve maximum efficiency, getMQObj returns the lower triangular part of this matrix only.

Obtain the current SLP solution values

Convenience wrapper for GetObj(double[], int, int).

Convenience wrapper for GetObj(double[], int, int).

Returns the objective function coefficients for the columns in a given range.

Retrieves the value of a given double attribute associated with a multi-objective solve. When solving a multi-objective problem, several objectives might be optimized in sequence. After each solve, the problem attributes are captured so that they can be queried afterwards.

Retrieves the value of a given double control parameter associated with an objective function. These parameters control how the objective is treated during multi-objective optimization.

Function to access the type name of an object referenced using the generic Optimizer object pointer XPRSobject.

Retrieves the value of a given integer attribute associated with a multi-objective solve. When solving a multi-objective problem, several objectives might be optimized in sequence. After each solve, the problem attributes are captured so that they can be queried afterwards.

Retrieves the value of a given integer attribute associated with a multi-objective solve. When solving a multi-objective problem, several objectives might be optimized in sequence. After each solve, the problem attributes are captured so that they can be queried afterwards.

Retrieves the value of a given integer control parameter associated with an objective. These parameters control how the objective is treated during multi-objective optimization.

For a given objective function, returns the objective coefficients for the columns in a given range.

Returns the pivot order of the basic variables.

Returns a list of potential leaving variables if a specified variable enters the basis.

Returns the current basis from memory into the user's data areas. If the problem is presolved, the presolved basis will be returned. Otherwise the original basis will be returned.

Returns the mapping of the row and column numbers from the presolve problem back to the original problem.

Get a solution.

Returns the solution for the presolved problem from memory.

Returns the solution for the presolved problem from memory.

Get the djs values of a solution.

Get the duals values of a solution.

Get the slack values of a solution.

Get the x values of a solution.

Retrieves a primal ray (primal unbounded direction) for the current problem, if the problem is found to be unbounded.

Returns the current problem name.

Returns the current problem name.

Returns the piecewise linear constraints y = f(x) in a given range.

Returns the piecewise linear constraints y = f(x) in a given range.

Returns a single quadratic objective function coefficient corresponding to the variable pair (objqcol1, objqcol2) of the Hessian matrix.

Returns a single quadratic objective function coefficient corresponding to the variable pair (objqcol1, objqcol2) of the Hessian matrix.

Returns a single quadratic constraint coefficient corresponding to the variable pair (rowqcol1, rowqcol2) of the Hessian of a given constraint.

Returns a single quadratic constraint coefficient corresponding to the variable pair (rowqcol1, rowqcol2) of the Hessian of a given constraint.

Returns the nonzeros in a quadratic constraint coefficients matrix for the columns in a given range. To achieve maximum efficiency, getQRowQMatrix returns the lower triangular part of this matrix only.

Returns the nonzeros in a quadratic constraint coefficients matrix for the columns in a given range. To achieve maximum efficiency, getQRowQMatrix returns the lower triangular part of this matrix only.

Returns the nonzeros in a quadratic constraint coefficients matrix as triplets (index pairs with coefficients). To achieve maximum efficiency, getQRowQMatrixTriplets returns the lower triangular part of this matrix only.

Returns the nonzeros in a quadratic constraint coefficients matrix as triplets (index pairs with coefficients). To achieve maximum efficiency, getQRowQMatrixTriplets returns the lower triangular part of this matrix only.

Returns the list indices of the rows that have quadratic coefficients.

Returns the list indices of the rows that have quadratic coefficients.

Returns the list indices of the rows that have quadratic coefficients.

Used to obtain the reduced cost values following optimization with optimize.

Convenience wrapper for GetRHS(double[], int, int).

Convenience wrapper for GetRHS(double[], int, int).

Returns the right hand side elements for the rows in a given range.

Convenience wrapper for GetRHSRange(double[], int, int).

Convenience wrapper for GetRHSRange(double[], int, int).

Returns the right hand side range values for the rows in a given range.

Convenience wrapper for GetRowFlags(int[], int, int).

Convenience wrapper for GetRowFlags(int[], int, int).

Retrieve if a range of rows have been set up as special rows.

Returns the nonzeros in the constraint matrix for the rows in a given range.

Returns the nonzeros in the constraint matrix for the rows in a given range.

Returns the nonzeros in the constraint matrix for the rows in a given range.

Returns the nonzeros in the constraint matrix for the rows in a given range.

Convenience wrapper for GetRowType(char[], int, int).

Convenience wrapper for GetRowType(char[], int, int).

Returns the row types for the rows in a given range.

Returns the the current scaling of the matrix.

Returns a list of scaled infeasible primal and dual variables for the original problem. If the problem is currently presolved, it is postsolved before the function returns.

Used to obtain the slack values following optimization with optimize.

Get the djs values of a solution.

Get the duals values of a solution.

Get the slack values of a solution.

Used to obtain the solution following optimization with optimize.

Get the x values of a solution.

Returns the value of a given string control parameters.

Enables users to recover the values of various string problem attributes. Problem attributes are set during loading and optimization of a problem.

Gets the Type of the current instance.

Convenience wrapper for GetUB(double[], int, int).

Convenience wrapper for GetUB(double[], int, int).

Returns the upper bounds for the columns in a given range.

Returns the index vector which causes the primal simplex or dual simplex algorithm to determine that a matrix is primal or dual unbounded respectively.

Returns the index vector which causes the primal simplex or dual simplex algorithm to determine that a matrix is primal or dual unbounded respectively.

Performs an automated search for independent Irreducible Infeasible Sets (IIS) in an infeasible problem.

Performs the isolation identification procedure for an Irreducible Infeasible Set (IIS). This function applies only to linear problems.

Returns statistics on the Irreducible Infeasible Sets (IIS) found so far by firstIIS (IIS), nextIIS (IIS-n) or iISAll (IIS-a).

Interrupts the Optimizer algorithms.

Interrupts the Optimizer algorithms.

Loads a basis from the user's areas.

Convenience wrapper for LoadBranchDirs(int, int[], int[]).

Loads directives into the current problem to specify which MIP entities the Optimizer should continue to branch on when a node solution is integer feasible.

Loads cuts from the cut pool into the matrix. Without calling loadCuts the cuts will remain in the cut pool but will not be active at the node. Cuts loaded at a node remain active at all descendant nodes unless they are deleted using delCuts.

Loads cuts from the cut pool into the matrix. Without calling loadCuts the cuts will remain in the cut pool but will not be active at the node. Cuts loaded at a node remain active at all descendant nodes unless they are deleted using delCuts.

Loads cuts from the cut pool into the matrix. Without calling loadCuts the cuts will remain in the cut pool but will not be active at the node. Cuts loaded at a node remain active at all descendant nodes unless they are deleted using delCuts.

Specifies that a set of rows in the matrix will be treated as delayed rows during a tree search. These are rows that must be satisfied for any integer solution, but will not be loaded into the active set of constraints until required.

Loads directives into the matrix.

Enables the user to pass a matrix directly to the Optimizer, rather than reading the matrix from a file.

Enables the user to pass a matrix directly to the Optimizer, rather than reading the matrix from a file.

Loads an LP solution for the problem into the Optimizer.

Used to load a MIP problem into the Optimizer data structures. Integer, binary, partial integer, semi-continuous and semi-continuous integer variables can be defined, together with sets of type 1 and 2. The reference row values for the set members are passed as an array rather than specifying a reference row.

Used to load a MIP problem into the Optimizer data structures. Integer, binary, partial integer, semi-continuous and semi-continuous integer variables can be defined, together with sets of type 1 and 2. The reference row values for the set members are passed as an array rather than specifying a reference row.

Loads a starting MIP solution for the problem into the Optimizer.

Loads a starting MIP solution for the problem into the Optimizer.

Used to load a mixed integer quadratic problem with quadratic constraints into the Optimizer data structure. Such a problem may have quadratic terms in its objective function as well as in its constraints. Integer, binary, partial integer, semi-continuous and semi-continuous integer variables can be defined, together with sets of type 1 and 2. The reference row values for the set members are passed as an array rather than specifying a reference row.

Used to load a mixed integer quadratic problem with quadratic constraints into the Optimizer data structure. Such a problem may have quadratic terms in its objective function as well as in its constraints. Integer, binary, partial integer, semi-continuous and semi-continuous integer variables can be defined, together with sets of type 1 and 2. The reference row values for the set members are passed as an array rather than specifying a reference row.

Used to load a MIQP problem, hence a MIP with quadratic objective coefficients, into the Optimizer data structures. Integer, binary, partial integer, semi-continuous and semi-continuous integer variables can be defined, together with sets of type 1 and 2. The reference row values for the set members are passed as an array rather than specifying a reference row.

Used to load a MIQP problem, hence a MIP with quadratic objective coefficients, into the Optimizer data structures. Integer, binary, partial integer, semi-continuous and semi-continuous integer variables can be defined, together with sets of type 1 and 2. The reference row values for the set members are passed as an array rather than specifying a reference row.

Specifies that a set of rows in the matrix will be treated as model cuts.

Loads a presolved basis from the user's areas.

Loads directives into the presolved matrix.

Used to load a quadratic problem with quadratic side constraints into the Optimizer data structure. Such a problem may have quadratic terms in its objective function as well as in its constraints.

Used to load a quadratic problem with quadratic side constraints into the Optimizer data structure. Such a problem may have quadratic terms in its objective function as well as in its constraints.

Used to load a quadratic problem into the Optimizer data structure. Such a problem may have quadratic terms in its objective function, although not in its constraints.

Used to load a quadratic problem into the Optimizer data structure. Such a problem may have quadratic terms in its objective function, although not in its constraints.

Allows the user to mark rows and columns in order to prevent the presolve removing these rows and columns from the matrix.

This function begins a search for the optimal continuous (LP) solution. The direction of optimization is given by OBJSENSE. The status of the problem when the function completes can be checked using LPSTATUS. Any MIP entities in the problem will be ignored.

This function begins a search for the optimal continuous (LP) solution. The direction of optimization is given by OBJSENSE. The status of the problem when the function completes can be checked using LPSTATUS. Any MIP entities in the problem will be ignored.

Begins a search for the optimal LP solution. *@deprecated

Begins a search for the optimal LP solution. *@deprecated

Creates a shallow copy of the current Object.

Begins a search for the optimal LP solution. *@deprecated

Begins a search for the optimal LP solution. *@deprecated

This function begins a tree search for the optimal MIP solution. The direction of optimization is given by OBJSENSE. The status of the problem when the function completes can be checked using MIPSTATUS.

This function begins a tree search for the optimal MIP solution. The direction of optimization is given by OBJSENSE. The status of the problem when the function completes can be checked using MIPSTATUS.

A combined version of XSLPmsaddjob and XSLPmsaddpreset. The preset described is loaded, topped up with the specific settings supplied

Adds a multistart job to the multistart pool

Loads a preset of jobs into the multistart job pool.

Removes all scheduled jobs from the multistart job pool

Continues the search for further Irreducible Infeasible Sets (IIS), or calls firstIIS (IIS) if no IIS has been identified yet.

Continues the search for further Irreducible Infeasible Sets (IIS), or calls firstIIS (IIS) if no IIS has been identified yet.

Add non-linear formulas to the SLP problem.

Calculate the slack values for the provided solution in the non-linear problem

Add or replace a single matrix formula using a parsed or unparsed formula

Add or replace a single matrix formula using a character string for the formula.

Add or replace a single matrix formula using a character string for the formula. *@deprecated

Transfer the current solution to initial values

Delete nonlinear formulas from the current problem

Delete a user function from the current problem

Evaluate a formula using the current values of the variables

Retrieve a single matrix formula as a formula split into tokens.

Retrieve the list of positions of the nonlinear formulas in the problem

Retrieve a single matrix formula in a character string.

Retrieve a single matrix formula in a character string. *@deprecated

Imports a function from a library file to be called as a user function

Load non-linear formulas into the SLP problem

Maximize or minimize an SLP problem

Restores the problem to its pre-solve state

Print a summary of any evaluation errors that may have occurred during solving a problem

Set the function error flag for the problem

Convenience wrapper for NlpSetInitVal(int, int[], double[]).

Set the initial value of a variable

Validate the feasibility of constraints in a converged solution

Validates the first order optimality conditions also known as the Karush-Kuhn-Tucker (KKT) conditions versus the currect solution

Prints an extensive analysis on a given constraint of the SLP problem

Validate the feasibility of constraints for a given solution

Returns upper and lower sensitivity ranges for specified objective function coefficients. If the objective coefficients are varied within these ranges the current basis remains optimal and the reduced costs remain valid.

This function begins a search for the optimal solution of the problem. The direction of optimization is given by OBJSENSE.

Performs a simplex pivot by bringing variable enter into the basis and removing leave.

Postsolve the current matrix when it is in a presolved state.

Postsolves a primal solution formulated in the presolved space into the corresponding solution formulated in the original space. The problem itself is unchanged.

Presolves a row formulated in terms of the original variables such that it can be added to a presolved matrix.

Instructs the Optimizer to read in a previously saved basis from a file.

Instructs the Optimizer to read in a previously saved basis from a file.

Instructs the Optimizer to read in a previously saved basis from a file.

Reads a solution from a binary solution file.

Reads a solution from a binary solution file.

Reads a solution from a binary solution file.

Reads a directives file to help direct the tree search.

Reads a directives file to help direct the tree search.

Reads an (X)MPS or LP format matrix from file.

Reads an (X)MPS or LP format matrix from file.

Reads an ASCII solution file [.slx] created by the writeSlxSol function.

Reads an ASCII solution file [.slx] created by the writeSlxSol function.

Reads an ASCII solution file [.slx] created by the writeSlxSol function.

Executes the MIP solution refiner. *@deprecated

Remove AfterObjective callback.

Remove all AfterObjective callbacks.

Remove BarIteration callback.

Remove all BarIteration callbacks.

Remove Barlog callback.

Remove all Barlog callbacks.

Remove BeforeObjective callback.

Remove all BeforeObjective callbacks.

Remove BeforeSolve callback.

Remove all BeforeSolve callbacks.

Remove ChangeBranchObject callback.

Remove all ChangeBranchObject callbacks.

Remove CheckTime callback.

Remove all CheckTime callbacks.

Remove Chgbranch callback.

Remove all Chgbranch callbacks.

Remove Chgnode callback.

Remove all Chgnode callbacks.

Remove ComputeRestart callback.

Remove all ComputeRestart callbacks.

Remove Cutlog callback.

Remove all Cutlog callbacks.

Remove Cutmgr callback.

Remove all Cutmgr callbacks.

Remove Estimate callback.

Remove all Estimate callbacks.

Remove GapNotify callback.

Remove all GapNotify callbacks.

Remove Infnode callback.

Remove all Infnode callbacks.

Remove Intsol callback.

Remove all Intsol callbacks.

Remove Lplog callback.

Remove all Lplog callbacks.

Remove Message callback.

Remove all Message callbacks.

Remove Miplog callback.

Remove all Miplog callbacks.

Remove MipThread callback.

Remove all MipThread callbacks.

Remove MipThreadDestroy callback.

Remove all MipThreadDestroy callbacks.

Remove MsgHandler callback.

Remove all MsgHandler callbacks.

Remove MsJobEnd callback.

Remove all MsJobEnd callbacks.

Remove MsJobStart callback.

Remove all MsJobStart callbacks.

Remove MsWinner callback.

Remove all MsWinner callbacks.

Remove Newnode callback.

Remove all Newnode callbacks.

Remove NlpCoefEvalError callback.

Remove all NlpCoefEvalError callbacks.

Remove Nodecutoff callback.

Remove all Nodecutoff callbacks.

Remove NodeLPSolved callback.

Remove all NodeLPSolved callbacks.

Remove Optnode callback.

Remove all Optnode callbacks.

Remove PreIntsol callback.

Remove all PreIntsol callbacks.

Remove Prenode callback.

Remove all Prenode callbacks.

Remove Presolve callback.

Remove all Presolve callbacks.

Remove Sepnode callback.

Remove all Sepnode callbacks.

Remove SlpCascadeEnd callback.

Remove all SlpCascadeEnd callbacks.

Remove SlpCascadeStart callback.

Remove all SlpCascadeStart callbacks.

Remove SlpCascadeVar callback.

Remove all SlpCascadeVar callbacks.

Remove SlpCascadeVarFail callback.

Remove all SlpCascadeVarFail callbacks.

Remove SlpConstruct callback.

Remove all SlpConstruct callbacks.

Remove SlpDrCol callback.

Remove all SlpDrCol callbacks.

Remove SlpIntSol callback.

Remove all SlpIntSol callbacks.

Remove SlpIterEnd callback.

Remove all SlpIterEnd callbacks.

Remove SlpIterStart callback.

Remove all SlpIterStart callbacks.

Remove SlpIterVar callback.

Remove all SlpIterVar callbacks.

Remove SlpPreUpdateLinearization callback.

Remove all SlpPreUpdateLinearization callbacks.

Remove UserSolNotify callback.

Remove all UserSolNotify callbacks.

Provides a simplified interface for repairWeightedInfeas.

By relaxing a set of selected constraints and bounds of an infeasible problem, it attempts to identify a 'solution' that violates the selected set of constraints and bounds minimally, while satisfying all other constraints and bounds. Among such solution candidates, it selects one that is optimal regarding the original objective function. For the console version, see REPAIRINFEAS.

An extended version of repairWeightedInfeas that allows for bounding the level of relaxation allowed.

Restores the Optimizer's data structures from a file created by save (SAVE). Optimization may then recommence from the point at which the file was created.

Restores the Optimizer's data structures from a file created by save (SAVE). Optimization may then recommence from the point at which the file was created.

Restores the Optimizer's data structures from a file created by save (SAVE). Optimization may then recommence from the point at which the file was created.

Returns upper and lower sensitivity ranges for specified right hand side (RHS) function coefficients. If the RHS coefficients are varied within these ranges the current basis remains optimal and the reduced costs remain valid.

Saves the current data structures, i.e. matrices, control settings and problem attribute settings to file and terminates the run so that optimization can be resumed later.

Saves the current data structures, i.e. matrices, control settings and problem attribute settings to file and terminates the run so that optimization can be resumed later.

Re-scales the current matrix.

Specifies the bounds previously stored using storeBounds that are to be applied in order to branch on a user entity. This routine can only be called from the user separate callback function, addCbSepnode.

Specifies the pointers to cuts in the cut pool that are to be applied in order to branch on a user entity. This routine can only be called from the user separate callback function, addCbSepnode.

Sets the value of a given double control parameter.

Sets all controls to their default values. Must be called before the problem is read or loaded by readProb, loadMIP, loadLP, loadMIQP, loadQP.

Specifies that a set of rows in the matrix will be treated as indicator constraints during a tree search. An indicator constraint is made of a condition and a constraint. The condition is of the type "bin = value", where bin is a binary variable and value is either 0 or 1. The constraint is any matrix row (may be linear, quadratic or general nonlinear). During tree search, a row configured as an indicator constraint is enforced only when condition holds, that is only if the indicator variable bin has the specified value. Note that every row may only get assigned a single indicator variable and term. If a row needs to be activated by multiple different terms, the row needs to be duplicated so that each term can be assigned to a distinct row. If the indicator variable should be changed, the old term needs to be deleted first (by calling delIndicators or by calling this function with a comps argument of 0) before assigning a new one.

Sets the value of a given integer control parameter.

This directs all Optimizer output to a log file.

Sets the value of a given integer control parameter.

Manages suppression of messages.

Sets the value of a given double control parameter associated with an objective. These parameters control how the objective is treated during multi-objective optimization.

Sets the value of a given integer control parameter associated with an objective. These parameters control how the objective is treated during multi-objective optimization.

Sets the current default problem name. This command is rarely used.

Used to set the value of a given string control parameter.

Add non-linear coefficients to the SLP problem. For a simpler version of this function see XSLPaddformulas.

Establish a re-calculation sequence for SLP variables with determining rows.

Re-calculate consistent values for SLP variables based on the current values of the remaining variables.

Set a variable specific cascade iteration limit

Add or change a single matrix coefficient using a character string for the formula. For a simpler version of this function see nlpChgFormulaStr. *@deprecated

Add or change a single matrix coefficient using a parsed or unparsed formula. For a simpler version of this function see XSLPchgformula.

Add or change a single matrix coefficient using a character string for the formula. For a simpler version of this function see nlpChgFormulaStr.

Changes the type of the delta assigned to a nonlinear variable

Change the status setting of a constraint

Set or change the initial penalty error weight for a row

Create the full augmented SLP matrix and data structures, ready for optimization

Convenience wrapper for SlpDelCoefs(int, int[], int[]).

Delete coefficients from the current problem. For a simpler version of this function see XSLPdelformulas.

Evaluate a coefficient using the current values of the variables

Fixe the values of the error vectors

Retrieve a single matrix coefficient as a formula in a character string. For a simpler version of this function see nlpGetFormulaStr. *@deprecated

Retrieve a single matrix coefficient as a formula split into tokens. For a simpler version of this function see XSLPchgformula.

Retrieve the list of positions of the nonlinear coefficients in the problem. For a simpler version of this function see XSLPgetformularows.

Retrieve a single matrix coefficient as a formula in a character string. For a simpler version of this function see nlpGetFormulaStr.

Retrieve the status setting of a constraint

Get the initial penalty error weight for a row

Load non-linear coefficients into the SLP problem. For a simpler version of this function see XSLPloadformulas.

Reset the SLP problem to match a just augmented system

Convenience wrapper for SlpSetDetRow(int, int[], int[]).

Set the determining row of a variable

Removes the augmentation and returns the problem to its pre-linearization state

Updates the current linearization

Stores bounds for node separation using user separate callback function.

Stores bounds for node separation using user separate callback function.

Stores cuts into the cut pool, but does not apply them to the current node. These cuts must be explicitly loaded into the matrix using loadCuts or setBranchCuts before they become active.

Stores cuts into the cut pool, but does not apply them to the current node. These cuts must be explicitly loaded into the matrix using loadCuts or setBranchCuts before they become active.

Performs strong branching iterations on all specified bound changes. For each candidate bound change, strongBranch performs dual simplex iterations starting from the current optimal solution of the base LP, and returns both the status and objective value reached after these iterations.

Performs strong branching iterations on all specified bound changes. For each candidate bound change, strongBranchCB performs dual simplex iterations starting from the current optimal solution of the base LP, and returns both the status and objective value reached after these iterations.

Returns a String that represents the current Object.

This function begins a tuner session for the current problem. The tuner will solve the problem multiple times while evaluating a list of control settings and promising combinations of them. When finished, the tuner will select and set the best control setting on the problem. Note that the direction of optimization is given by OBJSENSE.

This function begins a tuner session for a set of problems. The tuner will solve the problems multiple times while evaluating a list of control settings and promising combinations of them. When finished, the tuner will select and set the best control setting on the problems.

This function loads a user defined tuner method from the given file.

This function writes the current tuner method to a given file or prints it to the console.

Unloads and frees all memory associated with the current problem. It also invalidates the current problem (as opposed to reading in an empty problem).

Writes the current basis to a file for later input into the Optimizer.

Writes the current basis to a file for later input into the Optimizer.

Writes the current basis to a file for later input into the Optimizer.

Writes the current MIP or LP solution to a binary solution file for later input into the Optimizer.

Writes the current MIP or LP solution to a binary solution file for later input into the Optimizer.

Writes the current MIP or LP solution to a binary solution file for later input into the Optimizer.

Writes the tree search directives from the current problem to a directives file.

Writes the tree search directives from the current problem to a directives file.

Writes an LP/MPS/CSV file containing a given Irreducible Infeasible Set (IIS). If 0 is passed as the IIS number parameter, the initial infeasible subproblem is written.

Writes an LP/MPS/CSV file containing a given Irreducible Infeasible Set (IIS). If 0 is passed as the IIS number parameter, the initial infeasible subproblem is written.

Writes the current problem to an MPS or LP file.

Writes the current problem to an MPS or LP file.

Writes the current problem to an MPS or LP file.

Writes the current solution to a fixed format ASCII file, problem_name.prt.

Writes the current solution to a fixed format ASCII file, problem_name.prt.

Writes the current solution to a fixed format ASCII file, problem_name.prt.

Creates an ASCII solution file (.slx) using a similar format to MPS files. These files can be read back into the Optimizer using the readSlxSol function.

Creates an ASCII solution file (.slx) using a similar format to MPS files. These files can be read back into the Optimizer using the readSlxSol function.

Creates an ASCII solution file (.slx) using a similar format to MPS files. These files can be read back into the Optimizer using the readSlxSol function.

Writes the current solution to a CSV format ASCII file, problem_name.asc (and .hdr).

Writes the current solution to a CSV format ASCII file, problem_name.asc (and .hdr).