XpressProblem

Field Detail

• NULL_VARIABLE

  public static final Variable NULL_VARIABLE

  Variable object that is used to indicate a constant term in expressions that are implemented as maps.

  Since:

  43.00

• callbacks

  public final XpressProblem.CallbackAPI callbacks

  Property through which callbacks for this instance can be accessed.

Constructor Detail

• XpressProblem

  public XpressProblem()

  Create a new problem without internal name. If not yet done then Xpress is initialized with the license found at the default license location. If Xpress is initialized this way then it will be automatically de-initialized once the newly created problem instance is closed.

  Since:

  43.00

• XpressProblem

  public XpressProblem​(java.lang.String problemName)

  Create a new problem with internal name. If not yet done then Xpress is initialized with the license found at the default license location. If Xpress is initialized this way then it will be automatically de-initialized once the newly created problem instance is closed.

  Parameters:

  problemName - Internal name of new problem, can be null.

  Since:

  43.00

• XpressProblem

  public XpressProblem​(java.lang.String problemName,
                       java.lang.String licensePath)

  Create a new problem with internal name and non-default license. If not yet done then Xpress is initialized with the license found at licensePath. If Xpress is initialized this way then it will be automatically de-initialized once the newly created problem instance is closed.

  Parameters:

  problemName - Internal name of new problem, can be null.

  licensePath - Path to license location. Can be null or the empty string to indicate that the license is in the default location.

  Since:

  43.00

Method Detail

• chgObj

  public XpressProblem chgObj​(Variable variable,
                              double coefficient)

  Change objective function coefficient. This changes the linear coefficient in the first/primary objective function. In order to delete a coefficient from the objective set it to 0 (zero).

  Used in these examples:

  • GlobalObjectiveParametrics
  • GoalProg

  Parameters:

  variable - Variable for which to change coefficient.

  coefficient - New coefficient for variables.

  Returns:

  Always returns this instance.

  Since:

  43.00

• chgObj

  public XpressProblem chgObj​(Variable[] variables,
                              double[] coefficients)

  Change objective function coefficients. This changes the linear coefficients in the first/primary objective function. In order to delete a coefficient from the objective set it to 0 (zero).

  Used in these examples:

  • GlobalObjectiveParametrics
  • GoalProg

  Parameters:

  variables - Variables for which to change coefficients.

  coefficients - New coefficients for variables.

  Returns:

  Always returns this instance.

  Since:

  43.00

• chgObjN

  public XpressProblem chgObjN​(int objidx,
                               Variable variable,
                               double coefficient)

  Change an objective function coefficient for a multi-objective problem. This changes the linear coefficient in the objective function objidx. In order to delete a coefficient from the objective set it to 0 (zero).

  Used in these examples:

  • GoalProg

  Parameters:

  objidx - Index of objective function to change,

  variable - Variable for which to change coefficient.

  coefficient - New coefficient for variable.

  Returns:

  Always returns this instance.

  Since:

  43.00

• chgObjN

  public XpressProblem chgObjN​(int objidx,
                               Variable[] variables,
                               double[] coefficients)

  Change objective function coefficients for a multi-objective problem. This changes tje linear coefficients in the objective function objidx. In order to delete a coefficient from the obejctive set it to 0 (zero).

  Used in these examples:

  • GoalProg

  Parameters:

  objidx - Index of objective function to change,

  variables - Variables for which to change coefficients.

  coefficients - New coefficients for variables.

  Returns:

  Always returns this instance.

  Since:

  43.00

• chgCoef

  public XpressProblem chgCoef​(Inequality row,
                               Variable variable,
                               double coefficient)

  Changes the coefficient for variable in row in the linear matrix.

  Parameters:

  row - Inequality in which to change coefficient.

  variable - Variable for which to change coefficient.

  coefficient - The new coefficient.

  Returns:

  Always returns this instance.

  Since:

  43.00

• chgCoefs

  public XpressProblem chgCoefs​(Inequality[] row,
                                Variable[] variable,
                                double[] coefficient)

  Change coefficients in the linear matrix. The function changes the coefficients as indicated by the triplets given by row, variable, coefficient.

  Parameters:

  row - Inequality in which to change coefficient.

  variable - Variable for which to change coefficient.

  coefficient - The new coefficient.

  Returns:

  Always returns this instance.

  Since:

  43.00

• variableForIndex

  public Variable variableForIndex​(int index)

  Map a variable index to a variable object.

  Parameters:

  index - Index to map.

  Returns:

  The variable for index.

  Since:

  43.00

  See Also:

  getVariables()

• variablesForIndices

  public Variable[] variablesForIndices​(int first,
                                        int last)

  Map a range of variable indices to variable objects.

  Parameters:

  first - First index to map.

  last - Last index to map.

  Returns:

  The variables from first (inclusive) through last (inclusive).

  Since:

  43.00

• delCols

  public void delCols​(int ncols,
                      int[] colind)

  Delete columns from this problem. Note that this may be expensive if you use Variable instances to formulate your problem since indices of remaining variables will have to be updated after columns were deleted from the underlying model. If you have to delete multiple variables then it is best to collect all variables to be deleted in an array and then delete all of them with a single call to this function.

  Overrides:

  delCols in class  XPRSprob

  Parameters:

  ncols - Number of columns to delete.

  colind - Indices of columns to delete.

  Since:

  43.00

• delVariables

  public void delVariables​(Variable[] vars)

  Delete variables from this problem.

  Parameters:

  vars - Variables to be deleted.

  Since:

  43.00

• getSolution

  public double[] getSolution​(Variable[] vars)

  Get the current solution for an array of variables. The values in the returned array are in 1-to-1 correspondence with the variables in vars.

  Parameters:

  vars - Variables for which solution is queried.

  Since:

  43.00

• getSolution

  public double[] getSolution​(java.util.Collection<Variable> vars)

  Get the current solution for a collection of variables. The values in the returned array are in 1-to-1 correspondence with the variables in vars.

  Used in these examples:

  • AddMipSol
  • GoalProg
  • Polygon
  • PolygonMap
  • PolygonMapDelta
  • PolygonMultiMap
  • PolygonMultiMapDelta
  • PolygonVecMap
  • PolygonVecMapDelta
  • Repair
  • RoundInt
  • TSP
  • Tableau
  • Trimloss

  Parameters:

  vars - Variables for which solution is queried.

  Returns:

  Solution values for vars.

  Since:

  43.00

• getSolution

  public double getSolution​(Variable v)

  Get the current solution for a single variable.

  Used in these examples:

  • AddMipSol
  • GoalProg
  • Polygon
  • PolygonMap
  • PolygonMapDelta
  • PolygonMultiMap
  • PolygonMultiMapDelta
  • PolygonVecMap
  • PolygonVecMapDelta
  • Repair
  • RoundInt
  • TSP
  • Tableau
  • Trimloss

  Parameters:

  v - Variable for which solution is queried.

  Returns:

  Solution for v.

  Since:

  43.00

• getRedCosts

  public double[] getRedCosts​(Variable[] vars)

  Get the reduced costs for an array of variables. The values in the returned array are in 1-to-1 correspondence with the variables in vars.

  Parameters:

  vars - Variables for which reduced costs are queried.

  Returns:

  Reduced costs for variables in vars.

  Since:

  43.00

• getRedCosts

  public double[] getRedCosts​(java.util.Collection<Variable> vars)

  Get the reduced costs for a collection of variables. The values in the returned array are in 1-to-1 correspondence with the variables in vars.

  Parameters:

  vars - Variables for which reduced costs are queried.

  Returns:

  Reduced costs for variables in vars.

  Since:

  43.00

• getRedCost

  public double getRedCost​(Variable v)

  Get the reduced cost for a single variable.

  Parameters:

  v - Variable for which reduced cost is queried.

  Returns:

  Reduced cost for v.

  Since:

  43.00

• getCallbackSolution

  public double[] getCallbackSolution​(Variable[] vars)

  Get the solution associated with the current callback for an array of variables. The values in the returned array are in 1-to-1 correspondence with the variables in vars.

  Used in these examples:

  • AddMipSol
  • Knapsack
  • MostViolated
  • SaveSol
  • TSP

  Parameters:

  vars - Variables for which solution is queried.

  Returns:

  Solution values for vars.

  Since:

  44.00

• getCallbackSolution

  public double[] getCallbackSolution​(java.util.Collection<Variable> vars)

  Get the solution associated with the current callback for a collection of variables. The values in the returned array are in 1-to-1 correspondence with the variables in vars.

  Used in these examples:

  • AddMipSol
  • Knapsack
  • MostViolated
  • SaveSol
  • TSP

  Parameters:

  vars - Variables for which solution is queried.

  Returns:

  Solution values for vars.

  Since:

  44.00

• getCallbackSolution

  public double getCallbackSolution​(Variable v)

  Get the solution associated with the current callback for a single variable.

  Used in these examples:

  • AddMipSol
  • Knapsack
  • MostViolated
  • SaveSol
  • TSP

  Parameters:

  v - Variable for which solution is queried.

  Returns:

  Solution for v.

  Since:

  44.00

• getCallbackRedCosts

  public double[] getCallbackRedCosts​(Variable[] vars)

  Get the reduced costs associated with the current callback for an array of variables. The values in the returned array are in 1-to-1 correspondence with the variables in vars.

  Parameters:

  vars - Variables for which reduced costs are queried.

  Returns:

  Reduced costs for variables in vars.

  Since:

  44.00

• getCallbackRedCosts

  public double[] getCallbackRedCosts​(java.util.Collection<Variable> vars)

  Get the reduced costs associated with the current callback for a collection of variables. The values in the returned array are in 1-to-1 correspondence with the variables in vars.

  Parameters:

  vars - Variables for which reduced costs are queried.

  Returns:

  Reduced costs for variables in vars.

  Since:

  44.00

• getCallbackRedCost

  public double getCallbackRedCost​(Variable v)

  Get the reduced cost associated with the current callbackfor a single variable.

  Parameters:

  v - Variable for which reduced cost is queried.

  Returns:

  Reduced cost for v.

  Since:

  44.00

• objSA

  public void objSA​(int len,
                    Variable[] variables,
                    double[] lower,
                    double[] upper)

  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.

  Parameters:

  len - Sensitivity analysis is performed only on the first len variables in variables.

  variables - Variables on which to perform sensitivity analysis.

  lower - Array of length at least len that receives the sensitivity analysis lower bounds.

  upper - Array of length at least len that receives the sensitivity analysis upper bounds.

  Since:

  43.00

• objSA

  public void objSA​(Variable[] variables,
                    double[] lower,
                    double[] upper)

  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.

  Parameters:

  variables - Variables on which to perform sensitivity analysis.

  lower - Array at least as long as variables that receives the sensitivity analysis lower bounds.

  upper - Array at least as long as variables that receives the sensitivity analysis upper bounds.

  Since:

  43.00

• bndSA

  public void bndSA​(int len,
                    Variable[] variables,
                    double[] lblower,
                    double[] lbupper,
                    double[] ublower,
                    double[] ubupper)

  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.

  Parameters:

  len - Sensitivity analysis is performed only on the first len variables in variables.

  variables - Variables on which to perform sensitivity analysis.

  lblower - Array of length at least len that receives the sensitivity analysis lower bounds for the variables' lower bound constraints.

  lbupper - Array of length at least len that receives the sensitivity analysis upper bounds for the variables' lower bound constraints.

  ublower - Array of length at least len that receives the sensitivity analysis lower bounds for the variables' upper bound constraints.

  ubupper - Array of length at least len that receives the sensitivity analysis upper bounds for the variables' upper bound constraints.

  Since:

  43.00

• bndSA

  public void bndSA​(Variable[] variables,
                    double[] lblower,
                    double[] lbupper,
                    double[] ublower,
                    double[] ubupper)

  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.

  Parameters:

  variables - Variables on which to perform sensitivity analysis.

  lblower - Array at least as long as variables that receives the sensitivity analysis lower bounds for the variables' lower bound constraints.

  lbupper - Array at least as long as variables that receives the sensitivity analysis upper bounds for the variables' lower bound constraints.

  ublower - Array at least as long as variables that receives the sensitivity analysis lower bounds for the variables' upper bound constraints.

  ubupper - Array at least as long as variables that receives the sensitivity analysis upper bounds for the variables' upper bound constraints.

  Since:

  43.00

• addMipSol

  public void addMipSol​(double[] values,
                        Variable[] variables,
                        java.lang.String name)

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

  Used in these examples:

  • AddMipSol
  • TSP

  Parameters:

  values - Values for variables.

  variables - Variables in the solution.

  name - Name for solution, can be null.

  Since:

  43.00

• getVariables

  public Variable[] getVariables()

  Get all the variables currently defined in this problem.

  Returns:

  All the variables in this problem.

  Since:

  43.00

  See Also:

  variableForIndex(int)

• chgBounds

  public void chgBounds​(Variable[] variables,
                        byte[] bndType,
                        double[] bndValue)

  Change bounds for multiple variables.

  Used in these examples:

  • AddMipSol
  • FixBV
  • RoundInt

  Parameters:

  variables - Variables for which to change bounds.

  bndType - Type of bounds to change.

  bndValue - New bounds.

  Since:

  43.00

• chgColType

  public void chgColType​(Variable[] variables,
                         ColumnType[] colType)

  Change types for multiple variables.

  Used in these examples:

  • Trimloss

  Parameters:

  variables - Variables for which to change types.

  colType - New column types.

  Since:

  43.00

• isNullVariable

  public static boolean isNullVariable​(Variable v)

  Check whether a variable is the same as NULL_VARIABLE. The NULL_VARIABLE is used in certain places to indicate the absence of a variable. For example, when iterating over the linear terms of an expression, a term with a NULL_VARIABLE indicates a constant term in the expression.

  Parameters:

  v - The variable to check.

  Returns:

  true if v is the null variable.

  Since:

  44.00

• slpSetDetRow

  public void slpSetDetRow​(Variable v,
                           Inequality i)

  Set the determining row of a variable.

  Parameters:

  v - Variable for which the determining row is set.

  i - Determining row for v.

  Since:

  44.00

• delIndicator

  public void delIndicator​(Inequality row)

  Delete a single indicator constraint. This only deletes the "indicator property from the specified row. Neither the associated variable nor the row are deleted.

  Parameters:

  row - Row from which to delete the indicator constraint.

  Since:

  43.00

• getIndicator

  public IndicatorObjects getIndicator​(Inequality row)

  Get indicator information for a single row.

  Parameters:

  row - The row to query.

  Returns:

  Indicator information for row. This will be null if row is not an indicator row.

  Since:

  43.00

• setIndicator

  public void setIndicator​(Variable indicatorVariable,
                           boolean indicatorValue,
                           Inequality row)

  Add an indicator constraint to this model. Both variable and row must exist.

  Parameters:

  indicatorVariable - Indicator variable.

  indicatorValue - Whether row becomes active if indicatorVariable is non-zero ( indicatorValue is true) or if indicatorVariable is zero ( indicatorValue is false).

  row - The implied row for the indicator constraint.

  Since:

  43.00

• setIndicators

  public void setIndicators​(Variable[] indicatorVariable,
                            boolean[] indicatorValue,
                            Inequality[] row)

  Add indicator constraints to this model. The provided arrays must all have length at least count and for any i in 0.. count-1 an indicator constraint is constructed from indicatorVariable[i], indicatorValue[i] and row[i]. If indicatorValue[i] is true then the constraints states that if indicatorVariable[i] is 1 (one), then row[i] must be satisfied (and if indicator is 0 (zero) then row[i] is ignored). Otherwise, row[i] must be satisfied if indicator[i] is 0 (zero) and is ignored otherwise. All referenced variables and rows must exist.

  Parameters:

  indicatorVariable - Indicator variables.

  indicatorValue - Whether rows become active if indicator variables are non-zero ( indicatorValue[.] is true) or if indicator variables are zero ( indicatorValue is false). If this is null or empty then rows become active if indicator variables are non-zero.

  row - The implied rows for the indicator constraints.

  Since:

  43.00

• setIndicators

  public <T> void setIndicators​(java.lang.Iterable<T> data,
                                java.util.function.Function<T,​Variable> indicatorVariable,
                                java.util.function.Function<T,​java.lang.Boolean> indicatorValue,
                                java.util.function.Function<T,​Inequality> row)

  Add indicator constraints to this model. The function iterates through data and calls the provided functions for each element found. The return values of the functions are used to construct an indicator constraint. For a fixed t, if indicatorValue(t) returns true then the created constraint states that if indicatorVariable(t) is 1 (one), then row(t) must be satisfied and is ignored otherwise. Otherwise, row(t) must be satisfied if indicatorVariable(t) is 0 (zero) and is ignored otherwise. All referenced variables and rows must exist.

  Type Parameters:

  T - Data type.

  Parameters:

  data - Data for which constraints are created.

  indicatorVariable - Indicator variables.

  indicatorValue - Whether indicator variables should be non-zero or zero for rows to become active. If this is null then rows become active if indicator variables are non-zero.

  row - The implied rows for the indicator constraints.

  Since:

  43.00

• setIndicators

  public <T> void setIndicators​(T[] data,
                                java.util.function.Function<T,​Variable> indicatorVariable,
                                java.util.function.Function<T,​java.lang.Boolean> indicatorValue,
                                java.util.function.Function<T,​Inequality> row)

  Add indicator constraints to this model. The function iterates through data and calls the provided functions for each element found. The return values of the functions are used to construct an indicator constraint. For a fixed t, if indicatorValue(t) returns true then the created constraint states that if indicatorVariable(t) is 1 (one), then row(t) must be satisfied and is ignored otherwise. Otherwise, row(t) must be satisfied if indicatorVariable(t) is 0 (zero) and is ignored otherwise. All referenced variables and rows must exist.

  Type Parameters:

  T - Data type.

  Parameters:

  data - Data for which constraints are created.

  indicatorVariable - Indicator variables.

  indicatorValue - Whether indicator variables should be non-zero or zero for rows to become active. If this is null then rows become active if indicator variables are non-zero.

  row - The implied rows for the indicator constraints.

  Since:

  43.00

• setIndicators

  public <T> void setIndicators​(java.util.Collection<T> data,
                                java.util.function.Function<T,​Variable> indicatorVariable,
                                java.util.function.Function<T,​java.lang.Boolean> indicatorValue,
                                java.util.function.Function<T,​Inequality> row)

  Add indicator constraints to this model. The function iterates through data and calls the provided functions for each element found. The return values of the functions are used to construct an indicator constraint. For a fixed t, if indicatorValue(t) returns true then the created constraint states that if indicatorVariable(t) is 1 (one), then row(t) must be satisfied and is ignored otherwise. Otherwise, row(t) must be satisfied if indicatorVariable(t) is 0 (zero) and is ignored otherwise. All referenced variables and rows must exist.

  Type Parameters:

  T - Data type.

  Parameters:

  data - Data for which constraints are created.

  indicatorVariable - Indicator variables.

  indicatorValue - Whether indicator variables should be non-zero or zero for rows to become active. If this is null then rows become active if indicator variables are non-zero.

  row - The implied rows for the indicator constraints.

  Since:

  43.00

• setIndicators

  public <T> void setIndicators​(java.util.stream.Stream<T> data,
                                java.util.function.Function<T,​Variable> indicatorVariable,
                                java.util.function.Function<T,​java.lang.Boolean> indicatorValue,
                                java.util.function.Function<T,​Inequality> row)

  Add indicator constraints to this model. The function iterates through data and calls the provided functions for each element found. The return values of the functions are used to construct an indicator constraint. For a fixed t, if indicatorValue(t) returns true then the created constraint states that if indicatorVariable(t) is 1 (one), then row(t) must be satisfied and is ignored otherwise. Otherwise, row(t) must be satisfied if indicatorVariable(t) is 0 (zero) and is ignored otherwise. All referenced variables and rows must exist.

  Type Parameters:

  T - Data type.

  Parameters:

  data - Data for which constraints are created.

  indicatorVariable - Indicator variables.

  indicatorValue - Whether indicator variables should be non-zero or zero for rows to become active. If this is null then rows become active if indicator variables are non-zero.

  row - The implied rows for the indicator constraints.

  Since:

  43.00

• setIndicators

  public void setIndicators​(int count,
                            java.util.function.Function<java.lang.Integer,​Variable> indicatorVariable,
                            java.util.function.Function<java.lang.Integer,​java.lang.Boolean> indicatorValue,
                            java.util.function.Function<java.lang.Integer,​Inequality> row)

  Add indicator constraints to this model. The function iterates through [0, ... ,count[ and calls the provided functions for each in this interval. The return values of the functions are used to construct an indicator constraint. For a fixed t, if indicatorValue(t) returns true then the created constraint states that if indicatorVariable(t) is 1 (one), then row(t) must be satisfied and is ignored otherwise. Otherwise, row(t) must be satisfied if indicatorVariable(t) is 0 (zero) and is ignored otherwise. All referenced variables and rows must exist.

  Parameters:

  count - How many constraint to add.

  indicatorVariable - Indicator variables.

  indicatorValue - Whether indicator variables should be non-zero or zero for rows to become active. If this is null then rows become active if indicator variables are non-zero.

  row - The implied rows for the indicator constraints.

  Since:

  43.00

• setIndicators

  public void setIndicators​(int[] data,
                            java.util.function.IntFunction<Variable> indicatorVariable,
                            java.util.function.IntFunction<java.lang.Boolean> indicatorValue,
                            java.util.function.IntFunction<Inequality> row)

  Add indicator constraints to this model. The function iterates through data and calls the provided functions for each element found. The return values of the functions are used to construct an indicator constraint. For a fixed t, if indicatorValue(t) returns true then the created constraint states that if indicatorVariable(t) is 1 (one), then row(t) must be satisfied and is ignored otherwise. Otherwise, row(t) must be satisfied if indicatorVariable(t) is 0 (zero) and is ignored otherwise. All referenced variables and rows must exist.

  Parameters:

  data - Data for which constraints are created.

  indicatorVariable - Indicator variables.

  indicatorValue - Whether indicator variables should be non-zero or zero for rows to become active. If this is null then rows become active if indicator variables are non-zero.

  row - The implied rows for the indicator constraints.

  Since:

  43.00

• setIndicators

  public void setIndicators​(java.util.stream.IntStream data,
                            java.util.function.IntFunction<Variable> indicatorVariable,
                            java.util.function.IntFunction<java.lang.Boolean> indicatorValue,
                            java.util.function.IntFunction<Inequality> row)

  Add indicator constraints to this model. The function iterates through data and calls the provided functions for each element found. The return values of the functions are used to construct an indicator constraint. For a fixed t, if indicatorValue(t) returns true then the created constraint states that if indicatorVariable(t) is 1 (one), then row(t) must be satisfied and is ignored otherwise. Otherwise, row(t) must be satisfied if indicatorVariable(t) is 0 (zero) and is ignored otherwise. All referenced variables and rows must exist.

  Parameters:

  data - Data for which constraints are created.

  indicatorVariable - Indicator variables.

  indicatorValue - Whether indicator variables should be non-zero or zero for rows to become active. If this is null then rows become active if indicator variables are non-zero.

  row - The implied rows for the indicator constraints.

  Since:

  43.00

• repairWeightedInfeas

  public int repairWeightedInfeas​(java.util.Map<Inequality,​java.lang.Double> lepref,
                                  java.util.Map<Inequality,​java.lang.Double> gepref,
                                  java.util.Map<Variable,​java.lang.Double> lbpref,
                                  java.util.Map<Variable,​java.lang.Double> ubpref,
                                  char phase2,
                                  double delta,
                                  java.lang.String flags)

  Repair infeasibilities using weights. 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.

  Used in these examples:

  • Repair

  Parameters:

  lepref - Map with preferences for relaxing the less-than-or-equal direction of rows. Inequalities without preference will not be relaxed. Can be null.

  gepref - Map with preferences for relaxing the greater-than-or-equal direction of rows. Inequalities without preference will not be relaxed. Can be null.

  lbpref - Map with preferences for relaxing the lower bounds of variables. Variables without preference will not be relaxed. Can be null.

  ubpref - Map with preferences for relaxing the upper bounds of variables. Variables without preference will not be relaxed. Can be null.

  phase2 - Controls the second phase of optimization.

  delta - Relaxation multiplier in second phase - 1.

  flags - Flags passed to the optimizer.

  Returns:

  Result status.

  Since:

  43.00

• getSOSs

  public SOS[] getSOSs()

  Get all the special ordered set constraints currently defined in this problem.

  Returns:

  All special ordered set constraints in this problem.

  Since:

  44.00

  See Also:

  sosForIndex(int)

• sosForIndex

  public SOS sosForIndex​(int index)

  Map an SOS index to an SOS object.

  Parameters:

  index - Index to map.

  Returns:

  The SOS for index.

  Since:

  43.00

  See Also:

  getSOSs()

• sosForIndices

  public SOS[] sosForIndices​(int first,
                             int last)

  Map a range of SOS indices to SOS objects.

  Parameters:

  first - First index to map.

  last - Last index to map.

  Since:

  43.00

• delSets

  public void delSets​(int nsets,
                      int[] sosind)

  Delete sets from this problem. Note that this may be expensive if you use SOS instances to formulate your problem since indices of remaining sets will have to be updated after sets were deleted from the underlying model. If you have to delete multiple sets then it is best to collect all sets to be deleted in an array and then delete all of them with a single call to this function.

  Overrides:

  delSets in class  XPRSprob

  Parameters:

  nsets - Number of sets to delete.

  sosind - Indices of sets to delete.

  Since:

  43.00

• delSOS

  public void delSOS​(SOS[] soss)

  Delete special ordered set constraints. Removes all the specified special ordered set constraints from this problem.

  Parameters:

  soss - SOS to be deleted.

  Since:

  43.00

• delSOS

  public void delSOS​(SOS sos)

  Delete a single SOS from the problem.

  Parameters:

  sos - SOS to delete.

  Since:

  43.00

• getPWLs

  public PWL[] getPWLs()

  Get all piecewise linear constraints currently defined in this problem.

  Returns:

  All piecewise linear constraints in this problem.

  Since:

  44.00

  See Also:

  pwlForIndex(int)

• pwlForIndex

  public PWL pwlForIndex​(int index)

  Map a PWL index to a PWL object.

  Parameters:

  index - Index to map.

  Returns:

  The PWL for index.

  Since:

  43.00

  See Also:

  getPWLs()

• pwlsForIndices

  public PWL[] pwlsForIndices​(int first,
                              int last)

  Map a range of PWL indices to PWL objects.

  Parameters:

  first - First index to map.

  last - Last index to map.

  Returns:

  The SOSs from first (inclusive).

  Since:

  43.00

• delPwlCons

  public void delPwlCons​(int npwls,
                         int[] pwlind)

  Delete piecewise linear constraints from this problem. Note that this may be expensive if you use PWL instances to formulate your problem since indices of remaining variables will have to be updated after columns were deleted from the underlying model. If you have to delete multiple variables then it is best to collect all variables to be deleted in an array and then delete all of them with a single call to this function.

  Overrides:

  delPwlCons in class  XPRSprob

  Parameters:

  npwls - Number of constraints to delete.

  pwlind - Indices of constraints to delete.

  Since:

  43.00

• delPwlConstraints

  public void delPwlConstraints​(PWL[] pwls)

  Delete PWL constraints from this problem.

  Parameters:

  pwls - Piecewise linear constraints to be deleted.

  Since:

  43.00

• getIIS

  public IIS getIIS​(int iis)

  Get the specified IIS.

  Parameters:

  iis - The index of the IIS for which data is queried.

  Returns:

  The IIS specified by iis.

  Since:

  43.00

• getGeneralConstraints

  public GeneralConstraint[] getGeneralConstraints()

  Get all the general constraints currently defined in this problem.

  Returns:

  All general constraints in this problem.

  Since:

  43.00

  See Also:

  generalConstraintForIndex(int)

• generalConstraintForIndex

  public GeneralConstraint generalConstraintForIndex​(int index)

  Map a general constraint index to a GeneralConstraint object.

  Parameters:

  index - The index to map.

  Returns:

  The GeneralConstraint object for index.

  Since:

  43.00

  See Also:

  getGeneralConstraints()

• generalConstraintForIndices

  public GeneralConstraint[] generalConstraintForIndices​(int first,
                                                         int last)

  Map a range of general constraint indices to GeneralConstraint objects.

  Parameters:

  first - First index in range (inclusive).

  last - Last index in range (inclusive).

  Returns:

  The GeneralConstraint objects in the specified range.

  Since:

  43.00

• delGenCons

  public void delGenCons​(int nconstraints,
                         int[] conind)

  Delete constraints from this problem. Note that this may be expensive if you use GeneralConstraint instances to formulate your problem since indices of remaining constraints will have to be updated after constraints were deleted from the underlying model. If you have to delete multiple constraints then it is best to collect all constraints to be deleted in an array and then delete all of them with a single call to this function.

  Overrides:

  delGenCons in class  XPRSprob

  Parameters:

  nconstraints - Number of constraints to delete.

  conind - Indices of constraints to delete.

  Since:

  43.00

• delGeneralConstraints

  public void delGeneralConstraints​(GeneralConstraint[] constraints)

  Delete general constraints from this problem.

  Parameters:

  constraints - The constraints to be deleted.

  Since:

  43.00

• getCoef

  public double getCoef​(Inequality row,
                        Variable variable)

  Query a single coefficient from the linear matrix. Retrieves the coefficient of variable in row in the linear matrix. Note that the coefficient will be 0 (zero) in case the variable has no coefficient in that row.

  Parameters:

  row - The row in which to query the coefficient.

  variable - The variable for which to query the coefficient.

  Returns:

  The queried coefficient.

  Since:

  43.00

• getObj

  public double getObj​(Variable variable)

  Query an objective function coefficient. Retrieves the linear objective coefficient for the specified variable from the first/primary objective.

  Used in these examples:

  • Knapsack

  Parameters:

  variable - The variable for which to query the objective.

  Returns:

  The objective coefficient for variable.

  Since:

  43.00

• getObjN

  public double getObjN​(int objidx,
                        Variable variable)

  Query an objective function coefficient. Retrieves the linear objective coefficient for the specified variable from objective objidx.

  Parameters:

  objidx - objects.Index of objective function to query.

  variable - The variable for which to query the objective.

  Returns:

  The objective coefficient for variable.

  Since:

  43.00

• addConstraints

  public <T,​C extends Index> java.util.stream.Stream<java.util.Map.Entry<T,​C>> addConstraints​(java.util.Iterator<T> data,
                                                                                                          java.util.function.Function<T,​ConstraintDefinition<C>> defs)

  Add multiple constraints of the same type to the problem. Calls the specified functions for each element in data and adds a constraint as specified by the return values of the functions.

  Type Parameters:

  T - Data type.

  C - Constraint type.

  Parameters:

  data - Data to generate constraints.

  defs - Function to produce the constraint definitions.

  Returns:

  The created constraint indexed by data.

  Since:

  43.00

• addConstraint

  public <C extends Index> C addConstraint​(ConstraintDefinition<C> def)

  Add a single constraint to this problem.

  Type Parameters:

  C - Constraint type.

  Parameters:

  def - Definition of the constraint to add.

  Returns:

  The new constraint.

  Since:

  43.00

• addConstraints

  public <C extends Index,​T extends ConstraintDefinition<C>> java.util.stream.Stream<C> addConstraints​(java.util.stream.Stream<T> defs)

  Add multiple constraints of the same type to the problem.

  Type Parameters:

  C - Constraint type.

  T - Definition type.

  Parameters:

  defs - The constraints to add.

  Returns:

  The new constraints.

  Since:

  43.00

• addConstraints

  public <C extends Index,​T extends ConstraintDefinition<C>> java.util.stream.Stream<C> addConstraints​(java.lang.Iterable<T> defs)

  Add multiple constraints of the same type to the problem.

  Type Parameters:

  C - Constraint type.

  T - Definition type.

  Parameters:

  defs - The constraints to add.

  Returns:

  The new constraints.

  Since:

  43.00

• addConstraints

  public <C extends Index> java.util.stream.Stream<C> addConstraints​(ConstraintDefinition<C>[] defs)

  Add multiple of the same type constraints to the problem.

  Type Parameters:

  C - Constraint type.

  Parameters:

  defs - The constraints to add.

  Returns:

  The new constraints.

  Since:

  43.00

• addConstraints

  public <C extends Index> java.util.stream.Stream<C> addConstraints​(int count,
                                                                     java.util.function.IntFunction<ConstraintDefinition<C>> defs)

  Add multiple constraints of the same type to the problem. Calls the specified function for each element in [0, ..., count[ and adds a constraint as specified by the return value of the function.

  Type Parameters:

  C - Constraint type.

  Parameters:

  count - Number of constraints to add.

  defs - Function to produce the constraints to add.

  Returns:

  The new constraints.

  Since:

  43.00

• addConstraints

  public <T,​C extends Index> java.util.stream.Stream<C> addConstraints​(java.util.stream.Stream<T> data,
                                                                             java.util.function.Function<T,​ConstraintDefinition<C>> defs)

  Add multiple constraints of the same type to the problem. Calls the specified function for each element in data and adds a constraint as specified by the return value of the function.

  Type Parameters:

  T - Data type.

  C - Constraint type.

  Parameters:

  data - Data to generate constraints.

  defs - Function to generate a constraint for each data element.

  Returns:

  The new constraints.

  Since:

  43.00

• addConstraints

  public <T,​C extends Index> java.util.stream.Stream<C> addConstraints​(T[] data,
                                                                             java.util.function.Function<T,​ConstraintDefinition<C>> defs)

  Add multiple constraints of the same type to the problem. Calls the specified function for each element in data and adds a constraint as specified by the return value of the function.

  Type Parameters:

  T - Data type

  C - Constraint type.

  Parameters:

  data - Data to generate constraints.

  defs - Function to generate a constraint for each data element.

  Returns:

  The new constraints.

  Since:

  43.00

• addConstraints

  public <T,​C extends Index> java.util.stream.Stream<C> addConstraints​(java.lang.Iterable<T> data,
                                                                             java.util.function.Function<T,​ConstraintDefinition<C>> defs)

  Add multiple constraints of the same type to the problem. Calls the specified function for each element in data and adds a constraint as specified by the return value of the function.

  Type Parameters:

  T - Data type

  C - Constraint type.

  Parameters:

  data - Data for the constraints.

  defs - Function to generate a constraint for each data element.

  Returns:

  The new constraints.

  Since:

  43.00

• addConstraints

  public <C extends Index> java.util.stream.Stream<C> addConstraints​(int[] data,
                                                                     java.util.function.IntFunction<ConstraintDefinition<C>> defs)

  Add multiple constraints of the same type to the problem. Calls the specified function for each element in data and adds a constraint as specified by the return value of the function.

  Type Parameters:

  C - Constraint type.

  Parameters:

  data - Data to generate constraints.

  defs - Function to generate a constraint for each data item.

  Returns:

  The new constraints.

  Since:

  43.00

• addConstraints

  public <C extends Index> java.util.stream.Stream<C> addConstraints​(java.util.stream.IntStream data,
                                                                     java.util.function.IntFunction<ConstraintDefinition<C>> defs)

  Add multiple constraints of the same type to the problem. Calls the specified function for each element in data and adds a constraint as specified by the return value of the function.

  Type Parameters:

  C - Constraint type.

  Parameters:

  data - Data to generate constraints.

  defs - Function to generate a constraint for each data element.

  Returns:

  The new constraints.

  Since:

  43.00

• getInequalityLinear

  @Deprecated
  public LinTermList getInequalityLinear​(Inequality row)

  Deprecated.

  since 44.00, Use getLhs() instead
  Get the linear part of the left-hand side of a row.

  Parameters:

  row - The row for which the linear part is queried.

  Returns:

  The linear part of the row. This is guaranteed to not have any duplicates.

  Since:

  43.00

• getInequalityLinear

  public LinExpression getInequalityLinear​(Inequality row,
                                           java.util.function.Supplier<LinExpression> expression)

  Get the linear part of the left-hand side of a row. The function adds the linear part of row to the expression provided by expression. If expression is null then the function allocates a new com.dashoptimization.objects.LinTermList for it. If the function allocates a new com.dashoptimization.objects.LinTermList then it also returns that new object. In that case the list is guaranteed to not have any duplicates.

  Parameters:

  row - The row for which the linear part is queried.

  expression - Creates the expression that is returned by this function. Can be null in which case a new com.dashoptimization.objects.LinTermList is created.

  Returns:

  An expression that represent the linear part of the given row.

  Since:

  43.00

• inequalityForIndex

  public Inequality inequalityForIndex​(int index)

  Map an inequality index to an inequality object.

  Parameters:

  index - Index to map.

  Returns:

  The inequality for index.

  Since:

  43.00

  See Also:

  getInequalities()

• inequalitiesForIndices

  public Inequality[] inequalitiesForIndices​(int first,
                                             int last)

  Map a range of inequality indices to inequality objects.

  Parameters:

  first - First index to map.

  last - Last index to map.

  Since:

  43.00

• getInequalities

  public Inequality[] getInequalities()

  Get all the inequalities currently defined in this problem.

  Returns:

  All the inequalities in this problem.

  Since:

  43.00

  See Also:

  inequalityForIndex(int)

• delRows

  public void delRows​(int nrows,
                      int[] rowind)

  Delete rows from this problem. Note that this may be expensive if you use Inequality instances to formulate your problem since indices of remaining rows will have to be updated after rows were deleted from the underlying model. If you have to delete multiple rows then it is best to collect all rows to be deleted in an array and then delete all of them with a single call to this function.

  Overrides:

  delRows in class  XPRSprob

  Parameters:

  nrows - Number of rows to delete.

  rowind - Indices of rows to delete.

  Since:

  43.00

• delInequalities

  public void delInequalities​(Inequality[] rows)

  Delete inequality constraints from this problem.

  Parameters:

  rows - Inequalities to be deleted.

  Since:

  43.00

• getSlacks

  public double[] getSlacks​(Inequality[] rows)

  Get the current slacks for an array of rows. The values in the returned array are in 1-to-1 correspondence with the rows in rows.

  Used in these examples:

  • Repair
  • Tableau

  Parameters:

  rows - Inequalities for which to query slacks.

  Returns:

  Slacks for inequalities in rows.

  Since:

  43.00

• getSlacks

  public double[] getSlacks​(java.util.Collection<Inequality> rows)

  Get the current slacks for a collection of rows. The values in the returned array are in 1-to-1 correspondence with the rows in rows.

  Used in these examples:

  • Repair
  • Tableau

  Parameters:

  rows - Inequalities for which to query slacks.

  Returns:

  Slacks for inequalities in rows.

  Since:

  43.00

• getSlack

  public double getSlack​(Inequality r)

  Get the current slack for a single row.

  Parameters:

  r - Inequality for which to query slack.

  Returns:

  Slack for r.

  Since:

  43.00

• getDuals

  public double[] getDuals​(Inequality[] rows)

  Get the duals for an array of rows. The values in the returned array are in 1-to-1 correspondence with the rows in rows.

  Parameters:

  rows - Inequalities for which to query duals.

  Returns:

  Duals for inequalities in rows.

  Since:

  43.00

• getDuals

  public double[] getDuals​(java.util.Collection<Inequality> rows)

  Get the duals for a collection of rows. The values in the returned array are in 1-to-1 correspondence with the row in row.

  Parameters:

  rows - Inequalties for which to query duals.

  Returns:

  Duals for inequalities in rows.

  Since:

  43.00

• getDual

  public double getDual​(Inequality r)

  Get the dual for a single row.

  Parameters:

  r - Inequality for which to query dual.

  Returns:

  Dual for r.

  Since:

  43.00

• getCallbackSlacks

  public double[] getCallbackSlacks​(Inequality[] rows)

  Get the slacks associated with the current callback for an array of rows. The values in the returned array are in 1-to-1 correspondence with the rows in rows.

  Parameters:

  rows - Inequalities for which to query slacks.

  Returns:

  Slacks for inequalities in rows.

  Since:

  44.00

• getCallbackSlacks

  public double[] getCallbackSlacks​(java.util.Collection<Inequality> rows)

  Get the slacks associated with the current callback for a collection of rows. The values in the returned array are in 1-to-1 correspondence with the rows in rows.

  Parameters:

  rows - Inequalities for which to query slacks.

  Returns:

  Slacks for inequalities in rows.

  Since:

  44.00

• getCallbackSlack

  public double getCallbackSlack​(Inequality r)

  Get the slack associated with the current callback for a single row.

  Parameters:

  r - Inequality for which to query slack.

  Returns:

  Slack for r.

  Since:

  44.00

• getCallbackDuals

  public double[] getCallbackDuals​(Inequality[] rows)

  Get the duals associated with the current callback for an array of rows. The values in the returned array are in 1-to-1 correspondence with the rows in rows.

  Parameters:

  rows - Inequalities for which to query duals.

  Returns:

  Duals for inequalities in rows.

  Since:

  44.00

• getCallbackDuals

  public double[] getCallbackDuals​(java.util.Collection<Inequality> rows)

  Get the duals associated with the current callback for a collection of rows. The values in the returned array are in 1-to-1 correspondence with the row in row.

  Parameters:

  rows - Inequalties for which to query duals.

  Returns:

  Duals for inequalities in rows.

  Since:

  43.00

• getCallbackDual

  public double getCallbackDual​(Inequality r)

  Get the dual associated with the current callback for a single row.

  Parameters:

  r - Inequality for which to query dual.

  Returns:

  Dual for r.

  Since:

  44.00

• rhsSA

  public void rhsSA​(int len,
                    Inequality[] rows,
                    double[] lower,
                    double[] upper)

  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.

  Parameters:

  len - Sensitity analysis is only performed for the first len elements in rows.

  rows - The rows for which to perform sensitivity analysis.

  lower - Array of length at least len that receives the sensitivity lower bounds.

  upper - Array of length at least len that receives the sensitivity upper bounds.

  Since:

  43.00

• rhsSA

  public void rhsSA​(Inequality[] rows,
                    double[] lower,
                    double[] upper)

  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.

  Parameters:

  rows - The rows for which to perform sensitivity analysis.

  lower - Array at least as long as rows that receives the sensitivity lower bounds.

  upper - Array at least as long as rows that receives the sensitivity upper bounds.

  Since:

  43.00

• chgRHS

  public void chgRHS​(Inequality[] rows,
                     double[] newRHS)

  Change right-hand side for multiple rows.

  Used in these examples:

  • GlobalRHSParametrics
  • Repair

  Parameters:

  rows - Inequalities for which to change right-hand sides.

  newRHS - New right-hand side values.

  Since:

  43.00

• chgRowType

  public void chgRowType​(Inequality[] rows,
                         RowType[] rowType)

  Change types for multiple rows.

  Used in these examples:

  • Repair

  Parameters:

  rows - Inequalities for which to change types.

  rowType - New row types.

  Since:

  43.00

• chgRHSrange

  public void chgRHSrange​(Inequality[] rows,
                          double[] newRange)

  Change right-hand side ranges for multiple rows.

  Used in these examples:

  • Repair

  Parameters:

  rows - Inequalities for which to right-hand side ranges.

  newRange - New right-hand side range values.

  Since:

  43.00

• loadDelayedRows

  public void loadDelayedRows​(Inequality[] rows)

  Marks a set of rows as delayed rows.

  Parameters:

  rows - Inequalities to mark as delayed.

  Since:

  43.00

• loadModelCuts

  public void loadModelCuts​(Inequality[] rows)

  Marks a set of rows as model cuts.

  Parameters:

  rows - Inequalities to mark as model cuts.

  Since:

  43.00

• isOriginal

  public boolean isOriginal()

  Check whether this model instance is in the original state. A model is not in the original state if it is a callback problem or its problem state indicates being presolved.

  Used in these examples:

  • MostViolated

  Returns:

  true if this instance is in original state.

  Since:

  43.00

• addCut

  public int addCut​(int cuttype,
                    Inequality.Definition cut)

  Add a cut at the current node. It is assumed that the left-hand side ( lhs) is formulated in terms of the original model. So you can use Variable instances to formulate it. When using plain variable indices, be sure these indices are for the original model. The function will automatically transform (presolve) the cut to the presolved space. If presolving the cut fails then the cut is not added and the reason for failure is returned. Failing to presolve (and thus adding) a cut is not a problem in every context. That is why this does not raise an exception but instead leaves it to the caller to decide whether this is an error or not.

  Used in these examples:

  • TSP

  Parameters:

  cuttype - User defined cut type.

  cut - The inequality to add as cut.

  Returns:

  0 (zero) if the cut was successfully added. Otherwise the status code from presolveRow that indicates why the cut could not be presolved. It is up to the caller to decide whether not being able to presolve the cut is a problem or not.

  Since:

  43.00

• createBranchObject

  public XpressProblem.BranchObject createBranchObject()

  Create a new branch object. This is different from the super class's createBranchObject() function in two aspects: - it returns an instance of BranchObject, not XPRSbranchobject. The former is a subclass of the latter and has functions to add bounds and constraints that reference Variable objects. - the returned object always operates in the original space.

  Used in these examples:

  • MostViolated

  Returns:

  The new branch object.

  Since:

  43.00

• setObjective

  public void setObjective​(Expression obj)

  Set the objective function to a new expression.

  Used in these examples:

  • TSP

  Parameters:

  obj - The new objective

  Since:

  43.00

• setObjective

  public void setObjective​(Expression obj,
                           XPRSenumerations.ObjSense sense)

  Set the objective function to a new expression.

  Used in these examples:

  • TSP

  Parameters:

  obj - The new objective

  sense - The new objective sense (minimize or maximize).

  Since:

  43.00

• addObjective

  public void addObjective​(Expression obj,
                           int priority,
                           double weight)

  Add a new objective function. This turns the problem into a multi-objective problem.

  Parameters:

  obj - The new objective

  priority - Priority for new objective.

  weight - Weight for new objective.

  Since:

  43.00

• setObjective

  public void setObjective​(int idx,
                           Expression obj,
                           int priority,
                           double weight,
                           double abstol,
                           double reltol)

  Set an objective function and its controls. In case of error: - if the function created new objectives then all newly created objectives will be removed, - if an existing objective was modified then that objective function will be cleared and all controls will be unchanged.

  Used in these examples:

  • TSP

  Parameters:

  idx - Index of objective to set.

  obj - New objective for idx.

  priority - New objective priority.

  weight - New objective weight.

  abstol - New absolute tolerance for objective idx.

  reltol - New relative tolerance for objective idx.

  Since:

  43.00

• nlpSetInitVal

  public void nlpSetInitVal​(java.util.Map<Variable,​java.lang.Double> values)

  Set initial values of variables for a non-linear solve.

  Parameters:

  values - Values to be set. For each variable/value pair in this map the corresponding initial value is set.

  Since:

  43.00

• nlpSetInitVal

  public void nlpSetInitVal​(Variable[] variables,
                            double[] values)

  Set initial values of variables for a non-linear solve.

  Parameters:

  variables - Variables for which to set values.

  values - Values for variables. This must have the same length as variables. The initial value for variables[i] is values[i].

  Since:

  43.00

• getLhsExpression

  public Expression getLhsExpression​(int row)

  Get the left-hand side of a row as an expression.

  Parameters:

  row - Index of row to fetch.

  Returns:

  The left-hand side of row row.

  Since:

  43.00

• addConstraints

  public <C extends Index> void addConstraints​(int count1,
                                               int count2,
                                               java.util.function.BiFunction<java.lang.Integer,​java.lang.Integer,​ConstraintDefinition<C>> makeConstraint)

  Add multiple constraints to this problem. Calls makeConstraint for each element in the cartesian product of [0,count1[, ..., [0,countN[ and adds the constraint that is produced by this function call. A deep copy is made of each constraint, thus modifying the constraint later will not alter the model.

  Type Parameters:

  C - The type of constraints.

  Parameters:

  count1 - Length of dimension 1.

  count2 - Length of dimension 2.

  makeConstraint - Function to generate a constraint.

  Since:

  43.00

• addConstraints

  public <K1,​K2,​C extends Index> void addConstraints​(java.lang.Iterable<K1> iterable1,
                                                                 java.lang.Iterable<K2> iterable2,
                                                                 java.util.function.BiFunction<K1,​K2,​ConstraintDefinition<C>> makeConstraint)

  Add multiple constraints to this problem. Calls makeConstraint for each element in the cartesian product of the iterables and adds the constraint that is produced by this function call. A deep copy is made of each constraint, thus modifying the constraint later will not alter the model.

  Type Parameters:

  K1 - Data for dimension 1.

  K2 - Data for dimension 2.

  C - The type of constraints.

  Parameters:

  iterable1 - Keys for dimension 1.

  iterable2 - Keys for dimension 2.

  makeConstraint - Function to generate a constraint.

  Since:

  43.00

• addConstraints

  public <K1,​K2,​C extends Index> void addConstraints​(K1[] array1,
                                                                 K2[] array2,
                                                                 java.util.function.BiFunction<K1,​K2,​ConstraintDefinition<C>> makeConstraint)

  Add multiple constraints to this problem. Calls makeConstraint for each element in the cartesian product of the arrays and adds the constraint that is produced by this function call. A deep copy is made of each constraint, thus modifying the constraint later will not alter the model.

  Type Parameters:

  K1 - Data for dimension 1.

  K2 - Data for dimension 2.

  C - The type of constraints.

  Parameters:

  array1 - Data for dimension 1.

  array2 - Data for dimension 2.

  makeConstraint - Function to generate a constraint.

  Since:

  43.00

• addConstraints

  public <C extends Index> void addConstraints​(int count1,
                                               int count2,
                                               int count3,
                                               Function3<java.lang.Integer,​java.lang.Integer,​java.lang.Integer,​ConstraintDefinition<C>> makeConstraint)

  Add multiple constraints to this problem. Calls makeConstraint for each element in the cartesian product of [0,count1[, ..., [0,countN[ and adds the constraint that is produced by this function call. A deep copy is made of each constraint, thus modifying the constraint later will not alter the model.

  Type Parameters:

  C - The type of constraints.

  Parameters:

  count1 - Length of dimension 1.

  count2 - Length of dimension 2.

  count3 - Length of dimension 3.

  makeConstraint - Function to generate a constraint.

  Since:

  43.00

• addConstraints

  public <K1,​K2,​K3,​C extends Index> void addConstraints​(java.lang.Iterable<K1> iterable1,
                                                                          java.lang.Iterable<K2> iterable2,
                                                                          java.lang.Iterable<K3> iterable3,
                                                                          Function3<K1,​K2,​K3,​ConstraintDefinition<C>> makeConstraint)

  Add multiple constraints to this problem. Calls makeConstraint for each element in the cartesian product of the iterables and adds the constraint that is produced by this function call. A deep copy is made of each constraint, thus modifying the constraint later will not alter the model.

  Type Parameters:

  K1 - Data for dimension 1.

  K2 - Data for dimension 2.

  K3 - Data for dimension 3.

  C - The type of constraints.

  Parameters:

  iterable1 - Keys for dimension 1.

  iterable2 - Keys for dimension 2.

  iterable3 - Keys for dimension 3.

  makeConstraint - Function to generate a constraint.

  Since:

  43.00

• addConstraints

  public <K1,​K2,​K3,​C extends Index> void addConstraints​(K1[] array1,
                                                                          K2[] array2,
                                                                          K3[] array3,
                                                                          Function3<K1,​K2,​K3,​ConstraintDefinition<C>> makeConstraint)

  Add multiple constraints to this problem. Calls makeConstraint for each element in the cartesian product of the arrays and adds the constraint that is produced by this function call. A deep copy is made of each constraint, thus modifying the constraint later will not alter the model.

  Type Parameters:

  K1 - Data for dimension 1.

  K2 - Data for dimension 2.

  K3 - Data for dimension 3.

  C - The type of constraints.

  Parameters:

  array1 - Data for dimension 1.

  array2 - Data for dimension 2.

  array3 - Data for dimension 3.

  makeConstraint - Function to generate a constraint.

  Since:

  43.00

• addConstraints

  public <C extends Index> void addConstraints​(int count1,
                                               int count2,
                                               int count3,
                                               int count4,
                                               Function4<java.lang.Integer,​java.lang.Integer,​java.lang.Integer,​java.lang.Integer,​ConstraintDefinition<C>> makeConstraint)

  Add multiple constraints to this problem. Calls makeConstraint for each element in the cartesian product of [0,count1[, ..., [0,countN[ and adds the constraint that is produced by this function call. A deep copy is made of each constraint, thus modifying the constraint later will not alter the model.

  Type Parameters:

  C - The type of constraints.

  Parameters:

  count1 - Length of dimension 1.

  count2 - Length of dimension 2.

  count3 - Length of dimension 3.

  count4 - Length of dimension 4.

  makeConstraint - Function to generate a constraint.

  Since:

  43.00

• addConstraints

  public <K1,​K2,​K3,​K4,​C extends Index> void addConstraints​(java.lang.Iterable<K1> iterable1,
                                                                                   java.lang.Iterable<K2> iterable2,
                                                                                   java.lang.Iterable<K3> iterable3,
                                                                                   java.lang.Iterable<K4> iterable4,
                                                                                   Function4<K1,​K2,​K3,​K4,​ConstraintDefinition<C>> makeConstraint)

  Add multiple constraints to this problem. Calls makeConstraint for each element in the cartesian product of the iterables and adds the constraint that is produced by this function call. A deep copy is made of each constraint, thus modifying the constraint later will not alter the model.

  Type Parameters:

  K1 - Data for dimension 1.

  K2 - Data for dimension 2.

  K3 - Data for dimension 3.

  K4 - Data for dimension 4.

  C - The type of constraints.

  Parameters:

  iterable1 - Keys for dimension 1.

  iterable2 - Keys for dimension 2.

  iterable3 - Keys for dimension 3.

  iterable4 - Keys for dimension 4.

  makeConstraint - Function to generate a constraint.

  Since:

  43.00

• addConstraints

  public <K1,​K2,​K3,​K4,​C extends Index> void addConstraints​(K1[] array1,
                                                                                   K2[] array2,
                                                                                   K3[] array3,
                                                                                   K4[] array4,
                                                                                   Function4<K1,​K2,​K3,​K4,​ConstraintDefinition<C>> makeConstraint)

  Add multiple constraints to this problem. Calls makeConstraint for each element in the cartesian product of the arrays and adds the constraint that is produced by this function call. A deep copy is made of each constraint, thus modifying the constraint later will not alter the model.

  Type Parameters:

  K1 - Data for dimension 1.

  K2 - Data for dimension 2.

  K3 - Data for dimension 3.

  K4 - Data for dimension 4.

  C - The type of constraints.

  Parameters:

  array1 - Data for dimension 1.

  array2 - Data for dimension 2.

  array3 - Data for dimension 3.

  array4 - Data for dimension 4.

  makeConstraint - Function to generate a constraint.

  Since:

  43.00

• addConstraints

  public <C extends Index> void addConstraints​(int count1,
                                               int count2,
                                               int count3,
                                               int count4,
                                               int count5,
                                               Function5<java.lang.Integer,​java.lang.Integer,​java.lang.Integer,​java.lang.Integer,​java.lang.Integer,​ConstraintDefinition<C>> makeConstraint)

  Add multiple constraints to this problem. Calls makeConstraint for each element in the cartesian product of [0,count1[, ..., [0,countN[ and adds the constraint that is produced by this function call. A deep copy is made of each constraint, thus modifying the constraint later will not alter the model.

  Type Parameters:

  C - The type of constraints.

  Parameters:

  count1 - Length of dimension 1.

  count2 - Length of dimension 2.

  count3 - Length of dimension 3.

  count4 - Length of dimension 4.

  count5 - Length of dimension 5.

  makeConstraint - Function to generate a constraint.

  Since:

  43.00

• addConstraints

  public <K1,​K2,​K3,​K4,​K5,​C extends Index> void addConstraints​(java.lang.Iterable<K1> iterable1,
                                                                                            java.lang.Iterable<K2> iterable2,
                                                                                            java.lang.Iterable<K3> iterable3,
                                                                                            java.lang.Iterable<K4> iterable4,
                                                                                            java.lang.Iterable<K5> iterable5,
                                                                                            Function5<K1,​K2,​K3,​K4,​K5,​ConstraintDefinition<C>> makeConstraint)

  Add multiple constraints to this problem. Calls makeConstraint for each element in the cartesian product of the iterables and adds the constraint that is produced by this function call. A deep copy is made of each constraint, thus modifying the constraint later will not alter the model.

  Type Parameters:

  K1 - Data for dimension 1.

  K2 - Data for dimension 2.

  K3 - Data for dimension 3.

  K4 - Data for dimension 4.

  K5 - Data for dimension 5.

  C - The type of constraints.

  Parameters:

  iterable1 - Keys for dimension 1.

  iterable2 - Keys for dimension 2.

  iterable3 - Keys for dimension 3.

  iterable4 - Keys for dimension 4.

  iterable5 - Keys for dimension 5.

  makeConstraint - Function to generate a constraint.

  Since:

  43.00

• addConstraints

  public <K1,​K2,​K3,​K4,​K5,​C extends Index> void addConstraints​(K1[] array1,
                                                                                            K2[] array2,
                                                                                            K3[] array3,
                                                                                            K4[] array4,
                                                                                            K5[] array5,
                                                                                            Function5<K1,​K2,​K3,​K4,​K5,​ConstraintDefinition<C>> makeConstraint)

  Add multiple constraints to this problem. Calls makeConstraint for each element in the cartesian product of the arrays and adds the constraint that is produced by this function call. A deep copy is made of each constraint, thus modifying the constraint later will not alter the model.

  Type Parameters:

  K1 - Data for dimension 1.

  K2 - Data for dimension 2.

  K3 - Data for dimension 3.

  K4 - Data for dimension 4.

  K5 - Data for dimension 5.

  C - The type of constraints.

  Parameters:

  array1 - Data for dimension 1.

  array2 - Data for dimension 2.

  array3 - Data for dimension 3.

  array4 - Data for dimension 4.

  array5 - Data for dimension 5.

  makeConstraint - Function to generate a constraint.

  Since:

  43.00

• addVariables

  public VariableBuilder.VariableArrayBuilder addVariables​(int dim)

  Create an 1-dimensional array of variables. This function returns a builder that generates variables according to a specification. The specification can be modified. In order to actually create the variables, you have to call the returned builder's toArray() function.

     // Create a multi-dimensional array of binary variables
     com.dashoptimization.objects.Variable[]  = prob.addVariables(dim)
                           .withType(com.dashoptimization.objects.ColumnType.Binary)
                           .toArray();
    

  See VariableBuilder.VariableArrayBuilder for details of how to modify the specification in the builder.

  Parameters:

  dim - Dimension.

  Returns:

  A builder that will create the variables.

  Since:

  43.00

• addVariables

  public <K1> VariableBuilder.VariableMapBuilder<K1> addVariables​(java.util.Collection<K1> coll1)

  Create an 1-dimensional map of variables. This function returns a builder that generates variables according to a specification. The specification can be modified. In order to actually create the variables, you have to call the returned builder's toMap() function.

     // Create a multi-dimensional map of binary variables
     java.util.HashMap<K1 ,com.dashoptimization.objects.Variable> x = prob.addVariables(coll1 )
                                        .withType(com.dashoptimization.objects.ColumnType.Binary)
                                        .toMap();
    

  See VariableBuilder.VariableMapBuilder for details of how to modify the specification in the builder.

  Type Parameters:

  K1 - Data type for dimension 1.

  Parameters:

  coll1 - Data for dimension 1.

  Returns:

  A builder that will create the variables.

  Since:

  43.00

• addVariables

  public <K1> VariableBuilder.VariableMapBuilder<K1> addVariables​(K1[] arr1)

  Create an 1-dimensional map of variables. This function returns a builder that generates variables according to a specification. The specification can be modified. In order to actually create the variables, you have to call the returned builder's toMap() function.

     // Create a multi-dimensional array of binary columns
     java.util.HashMap<K1 ,com.dashoptimization.objects.Variable> x = prob.addVariables(coll1 )
                                        .withType(com.dashoptimization.objects.ColumnType.Binary)
                                        .toMap();
    

  See VariableBuilder.VariableMapBuilder for details of how to modify the specification in the builder.

  Type Parameters:

  K1 - Data type for dimension 1.

  Parameters:

  arr1 - Data for the builder.

  Returns:

  A builder that will create the variables.

  Since:

  43.00

• addVariables

  public <K1> VariableBuilder.VariableMapBuilder<K1> addVariables​(java.util.stream.Stream<K1> strm)

  Create an 1-dimensional map of variables. This function returns a builder that generates variables according to a specification. The specification can be modified. In order to actually create the variables, you have to call the returned builder's toMap() function.

     // Create a multi-dimensional array of binary columns
     java.util.HashMap<K1 ,com.dashoptimization.objects.Variable> x = prob.addVariables(coll1 )
                                        .withType(com.dashoptimization.objects.ColumnType.Binary)
                                        .toMap();
    

  See VariableBuilder.VariableMapBuilder for details of how to modify the specification in the builder.

  Type Parameters:

  K1 - Data type for dimension 1.

  Parameters:

  strm - Stream with data from which to generate variables.

  Returns:

  A builder that will create the variables.

  Since:

  43.00

• addVariable

  public Variable addVariable​(double lb,
                              double ub,
                              ColumnType type,
                              java.lang.String name)

  Add a single variable to this problem.

  Parameters:

  lb - Lower bound for new variable.

  ub - Upper bound for new variable.

  type - Type for new variable.

  name - Name for new variable, can be null.

  Returns:

  The newly created variable.

  Since:

  43.00

• addVariable

  public Variable addVariable​(double lb,
                              double ub,
                              ColumnType type,
                              double limit,
                              java.lang.String name)

  Add a single variable to this problem.

  Parameters:

  lb - Lower bound for new variable.

  ub - Upper bound for new variable.

  type - Type for new variable.

  limit - Global limit for the variable. This is ignored unless the variable is semi-continuous, semi-integer or partial integer.

  name - Name for new variable, can be null.

  Returns:

  The newly created variable.

  Since:

  43.00

• addVariable

  public Variable addVariable​(double lb,
                              double ub,
                              ColumnType type)

  Add a single variable to this problem.

  Parameters:

  lb - Lower bound for new variable.

  ub - Upper bound for new variable.

  type - Type for new variable.

  Returns:

  The newly created variable.

  Since:

  43.00

• addVariable

  public Variable addVariable​(java.lang.String name)

  Add a single variable to this problem. The variable will have default type (continuous) and bounds (0 and infinity).

  Parameters:

  name - Name for new variable.

  Returns:

  The newly created variable.

  Since:

  43.00

• addVariable

  public Variable addVariable​(ColumnType type)

  Add a single variable to this problem. The variable will have default bounds and no name.

  Parameters:

  type - Type for new variable.

  Returns:

  The newly created variable.

  Since:

  43.00

• addVariable

  public Variable addVariable​(ColumnType type,
                              java.lang.String name)

  Add a single variable to this problem. The variable will have default bounds.

  Parameters:

  type - Type for new variable.

  name - Name for new variable.

  Returns:

  The newly created variable.

  Since:

  43.00

• addVariable

  public Variable addVariable()

  Add a single variable to this problem. This variable will be continuous, have default bounds (0 and infinity) and will not have a name.

  Returns:

  The newly created variable.

  Since:

  43.00

• addVariables

  public VariableBuilder.VariableArray2Builder addVariables​(int dim1,
                                                            int dim2)

  Create an 2-dimensional array of variables. This function returns a builder that generates variables according to a specification. The specification can be modified. In order to actually create the variables, you have to call the returned builder's toArray() function.

     // Create a multi-dimensional array of binary variables
     com.dashoptimization.objects.Variable[] [] = prob.addVariables(dim1 ,dim2)
                           .withType(com.dashoptimization.objects.ColumnType.Binary)
                           .toArray();
    

  See VariableBuilder.VariableArray2Builder for details of how to modify the specification in the builder.

  Parameters:

  dim1 - Dimension 1.

  dim2 - Dimension 2.

  Returns:

  A builder that will create the variables.

  Since:

  43.00

• addVariables

  public <K1,​K2> VariableBuilder.VariableMap2Builder<K1,​K2> addVariables​(java.util.Collection<K1> coll1,
                                                                                     java.util.Collection<K2> coll2)

  Create an 2-dimensional map of variables. This function returns a builder that generates variables according to a specification. The specification can be modified. In order to actually create the variables, you have to call the returned builder's toMap() function.

     // Create a multi-dimensional map of binary variables
     com.dashoptimization.maps.HashMap2<K1 ,K2,com.dashoptimization.objects.Variable> x = prob.addVariables(coll1 ,coll2)
                                        .withType(com.dashoptimization.objects.ColumnType.Binary)
                                        .toMap();
    

  See VariableBuilder.VariableMap2Builder for details of how to modify the specification in the builder.

  Type Parameters:

  K1 - Data type for dimension 1.

  K2 - Data type for dimension 2.

  Parameters:

  coll1 - Data for dimension 1.

  coll2 - Data for dimension 2.

  Returns:

  A builder that will create the variables.

  Since:

  43.00

• addVariables

  public <K1,​K2> VariableBuilder.VariableMap2Builder<K1,​K2> addVariables​(K1[] arr1,
                                                                                     K2[] arr2)

  Create an 2-dimensional map of variables. This function returns a builder that generates variables according to a specification. The specification can be modified. In order to actually create the variables, you have to call the returned builder's toMap() function.

     // Create a multi-dimensional array of binary columns
     com.dashoptimization.maps.HashMap2<K1 ,K2,com.dashoptimization.objects.Variable> x = prob.addVariables(coll1 ,coll2)
                                        .withType(com.dashoptimization.objects.ColumnType.Binary)
                                        .toMap();
    

  See VariableBuilder.VariableMap2Builder for details of how to modify the specification in the builder.

  Type Parameters:

  K1 - Data type for dimension 1.

  K2 - Data type for dimension 2.

  Parameters:

  arr1 - Data for the builder.

  arr2 - Data for the builder.

  Returns:

  A builder that will create the variables.

  Since:

  43.00

• addVariables

  public VariableBuilder.VariableArray3Builder addVariables​(int dim1,
                                                            int dim2,
                                                            int dim3)

  Create an 3-dimensional array of variables. This function returns a builder that generates variables according to a specification. The specification can be modified. In order to actually create the variables, you have to call the returned builder's toArray() function.

     // Create a multi-dimensional array of binary variables
     com.dashoptimization.objects.Variable[] [] [] = prob.addVariables(dim1 ,dim2 ,dim3)
                           .withType(com.dashoptimization.objects.ColumnType.Binary)
                           .toArray();
    

  See VariableBuilder.VariableArray3Builder for details of how to modify the specification in the builder.

  Parameters:

  dim1 - Dimension 1.

  dim2 - Dimension 2.

  dim3 - Dimension 3.

  Returns:

  A builder that will create the variables.

  Since:

  43.00

• addVariables

  public <K1,​K2,​K3> VariableBuilder.VariableMap3Builder<K1,​K2,​K3> addVariables​(java.util.Collection<K1> coll1,
                                                                                                       java.util.Collection<K2> coll2,
                                                                                                       java.util.Collection<K3> coll3)

  Create an 3-dimensional map of variables. This function returns a builder that generates variables according to a specification. The specification can be modified. In order to actually create the variables, you have to call the returned builder's toMap() function.

     // Create a multi-dimensional map of binary variables
     com.dashoptimization.maps.HashMap3<K1 ,K2 ,K3,com.dashoptimization.objects.Variable> x = prob.addVariables(coll1 ,coll2 ,coll3)
                                        .withType(com.dashoptimization.objects.ColumnType.Binary)
                                        .toMap();
    

  See VariableBuilder.VariableMap3Builder for details of how to modify the specification in the builder.

  Type Parameters:

  K1 - Data type for dimension 1.

  K2 - Data type for dimension 2.

  K3 - Data type for dimension 3.

  Parameters:

  coll1 - Data for dimension 1.

  coll2 - Data for dimension 2.

  coll3 - Data for dimension 3.

  Returns:

  A builder that will create the variables.

  Since:

  43.00

• addVariables

  public <K1,​K2,​K3> VariableBuilder.VariableMap3Builder<K1,​K2,​K3> addVariables​(K1[] arr1,
                                                                                                       K2[] arr2,
                                                                                                       K3[] arr3)

  Create an 3-dimensional map of variables. This function returns a builder that generates variables according to a specification. The specification can be modified. In order to actually create the variables, you have to call the returned builder's toMap() function.

     // Create a multi-dimensional array of binary columns
     com.dashoptimization.maps.HashMap3<K1 ,K2 ,K3,com.dashoptimization.objects.Variable> x = prob.addVariables(coll1 ,coll2 ,coll3)
                                        .withType(com.dashoptimization.objects.ColumnType.Binary)
                                        .toMap();
    

  See VariableBuilder.VariableMap3Builder for details of how to modify the specification in the builder.

  Type Parameters:

  K1 - Data type for dimension 1.

  K2 - Data type for dimension 2.

  K3 - Data type for dimension 3.

  Parameters:

  arr1 - Data for the builder.

  arr2 - Data for the builder.

  arr3 - Data for the builder.

  Returns:

  A builder that will create the variables.

  Since:

  43.00

• addVariables

  public VariableBuilder.VariableArray4Builder addVariables​(int dim1,
                                                            int dim2,
                                                            int dim3,
                                                            int dim4)

  Create an 4-dimensional array of variables. This function returns a builder that generates variables according to a specification. The specification can be modified. In order to actually create the variables, you have to call the returned builder's toArray() function.

     // Create a multi-dimensional array of binary variables
     com.dashoptimization.objects.Variable[] [] [] [] = prob.addVariables(dim1 ,dim2 ,dim3 ,dim4)
                           .withType(com.dashoptimization.objects.ColumnType.Binary)
                           .toArray();
    

  See VariableBuilder.VariableArray4Builder for details of how to modify the specification in the builder.

  Parameters:

  dim1 - Dimension 1.

  dim2 - Dimension 2.

  dim3 - Dimension 3.

  dim4 - Dimension 4.

  Returns:

  A builder that will create the variables.

  Since:

  43.00

• addVariables

  public <K1,​K2,​K3,​K4> VariableBuilder.VariableMap4Builder<K1,​K2,​K3,​K4> addVariables​(java.util.Collection<K1> coll1,
                                                                                                                         java.util.Collection<K2> coll2,
                                                                                                                         java.util.Collection<K3> coll3,
                                                                                                                         java.util.Collection<K4> coll4)

  Create an 4-dimensional map of variables. This function returns a builder that generates variables according to a specification. The specification can be modified. In order to actually create the variables, you have to call the returned builder's toMap() function.

     // Create a multi-dimensional map of binary variables
     com.dashoptimization.maps.HashMap4<K1 ,K2 ,K3 ,K4,com.dashoptimization.objects.Variable> x = prob.addVariables(coll1 ,coll2 ,coll3 ,coll4)
                                        .withType(com.dashoptimization.objects.ColumnType.Binary)
                                        .toMap();
    

  See VariableBuilder.VariableMap4Builder for details of how to modify the specification in the builder.

  Type Parameters:

  K1 - Data type for dimension 1.

  K2 - Data type for dimension 2.

  K3 - Data type for dimension 3.

  K4 - Data type for dimension 4.

  Parameters:

  coll1 - Data for dimension 1.

  coll2 - Data for dimension 2.

  coll3 - Data for dimension 3.

  coll4 - Data for dimension 4.

  Returns:

  A builder that will create the variables.

  Since:

  43.00

• addVariables

  public <K1,​K2,​K3,​K4> VariableBuilder.VariableMap4Builder<K1,​K2,​K3,​K4> addVariables​(K1[] arr1,
                                                                                                                         K2[] arr2,
                                                                                                                         K3[] arr3,
                                                                                                                         K4[] arr4)

  Create an 4-dimensional map of variables. This function returns a builder that generates variables according to a specification. The specification can be modified. In order to actually create the variables, you have to call the returned builder's toMap() function.

     // Create a multi-dimensional array of binary columns
     com.dashoptimization.maps.HashMap4<K1 ,K2 ,K3 ,K4,com.dashoptimization.objects.Variable> x = prob.addVariables(coll1 ,coll2 ,coll3 ,coll4)
                                        .withType(com.dashoptimization.objects.ColumnType.Binary)
                                        .toMap();
    

  See VariableBuilder.VariableMap4Builder for details of how to modify the specification in the builder.

  Type Parameters:

  K1 - Data type for dimension 1.

  K2 - Data type for dimension 2.

  K3 - Data type for dimension 3.

  K4 - Data type for dimension 4.

  Parameters:

  arr1 - Data for the builder.

  arr2 - Data for the builder.

  arr3 - Data for the builder.

  arr4 - Data for the builder.

  Returns:

  A builder that will create the variables.

  Since:

  43.00

• addVariables

  public VariableBuilder.VariableArray5Builder addVariables​(int dim1,
                                                            int dim2,
                                                            int dim3,
                                                            int dim4,
                                                            int dim5)

  Create an 5-dimensional array of variables. This function returns a builder that generates variables according to a specification. The specification can be modified. In order to actually create the variables, you have to call the returned builder's toArray() function.

     // Create a multi-dimensional array of binary variables
     com.dashoptimization.objects.Variable[] [] [] [] [] = prob.addVariables(dim1 ,dim2 ,dim3 ,dim4 ,dim5)
                           .withType(com.dashoptimization.objects.ColumnType.Binary)
                           .toArray();
    

  See VariableBuilder.VariableArray5Builder for details of how to modify the specification in the builder.

  Parameters:

  dim1 - Dimension 1.

  dim2 - Dimension 2.

  dim3 - Dimension 3.

  dim4 - Dimension 4.

  dim5 - Dimension 5.

  Returns:

  A builder that will create the variables.

  Since:

  43.00

• addVariables

  public <K1,​K2,​K3,​K4,​K5> VariableBuilder.VariableMap5Builder<K1,​K2,​K3,​K4,​K5> addVariables​(java.util.Collection<K1> coll1,
                                                                                                                                           java.util.Collection<K2> coll2,
                                                                                                                                           java.util.Collection<K3> coll3,
                                                                                                                                           java.util.Collection<K4> coll4,
                                                                                                                                           java.util.Collection<K5> coll5)

  Create an 5-dimensional map of variables. This function returns a builder that generates variables according to a specification. The specification can be modified. In order to actually create the variables, you have to call the returned builder's toMap() function.

     // Create a multi-dimensional map of binary variables
     com.dashoptimization.maps.HashMap5<K1 ,K2 ,K3 ,K4 ,K5,com.dashoptimization.objects.Variable> x = prob.addVariables(coll1 ,coll2 ,coll3 ,coll4 ,coll5)
                                        .withType(com.dashoptimization.objects.ColumnType.Binary)
                                        .toMap();
    

  See VariableBuilder.VariableMap5Builder for details of how to modify the specification in the builder.

  Type Parameters:

  K1 - Data type for dimension 1.

  K2 - Data type for dimension 2.

  K3 - Data type for dimension 3.

  K4 - Data type for dimension 4.

  K5 - Data type for dimension 5.

  Parameters:

  coll1 - Data for dimension 1.

  coll2 - Data for dimension 2.

  coll3 - Data for dimension 3.

  coll4 - Data for dimension 4.

  coll5 - Data for dimension 5.

  Returns:

  A builder that will create the variables.

  Since:

  43.00

• addVariables

  public <K1,​K2,​K3,​K4,​K5> VariableBuilder.VariableMap5Builder<K1,​K2,​K3,​K4,​K5> addVariables​(K1[] arr1,
                                                                                                                                           K2[] arr2,
                                                                                                                                           K3[] arr3,
                                                                                                                                           K4[] arr4,
                                                                                                                                           K5[] arr5)

  Create an 5-dimensional map of variables. This function returns a builder that generates variables according to a specification. The specification can be modified. In order to actually create the variables, you have to call the returned builder's toMap() function.

     // Create a multi-dimensional array of binary columns
     com.dashoptimization.maps.HashMap5<K1 ,K2 ,K3 ,K4 ,K5,com.dashoptimization.objects.Variable> x = prob.addVariables(coll1 ,coll2 ,coll3 ,coll4 ,coll5)
                                        .withType(com.dashoptimization.objects.ColumnType.Binary)
                                        .toMap();
    

  See VariableBuilder.VariableMap5Builder for details of how to modify the specification in the builder.

  Type Parameters:

  K1 - Data type for dimension 1.

  K2 - Data type for dimension 2.

  K3 - Data type for dimension 3.

  K4 - Data type for dimension 4.

  K5 - Data type for dimension 5.

  Parameters:

  arr1 - Data for the builder.

  arr2 - Data for the builder.

  arr3 - Data for the builder.

  arr4 - Data for the builder.

  arr5 - Data for the builder.

  Returns:

  A builder that will create the variables.

  Since:

  43.00