Output Data Sets
This subsection describes the PRIMALOUT= and DUALOUT= output data sets. If the
SAVE_ONLY_IF_OPTIMAL option is not specified, the output data sets will not contain an intermediate solution.
Definitions of Variables in the PRIMALOUT= Data Set
The PRIMALOUT= data set contains the primal solution to the QP model. The variables in the data set have the following names and meanings.
- _OBJ_ID_
-
specifies the name of the objective function. This is particularly useful when there are multiple objective functions, in which case each objective function has a unique name.
See "ROWS Section" for details.
Note: PROC OPTQP does not support simultaneous optimization of multiple objective functions in this release.
- _RHS_ID_
-
specifies the name of the variable containing the right-hand-side value of each constraint.
See "ROWS Section" for details.
- _VAR_
-
specifies the name of the decision variable.
- _TYPE_
-
specifies the type of the decision variable. _TYPE_ can take one of the following values:
- N
- nonnegative variable
- D
- bounded variable with either lower or upper bound
- F
- free variable
- X
- fixed variable
- O
- other
- _OBJCOEF_
-
specifies the coefficient of the decision variable in the linear component of the objective function.
- _LBOUND_
-
specifies the lower bound on the decision variable.
- _UBOUND_
-
specifies the upper bound on the decision variable.
- _VALUE_
-
specifies the value of the decision variable.
- _STATUS_
-
specifies the status of the decision variable. _STATUS_ can indicate one of the following two cases:
- O
- QP problem is optimal.
- I
- QP problem could be infeasible or unbounded, or PROC OPTQP was not able to solve the problem.
Definitions of Variables in the DUALOUT= Data Set
The DUALOUT= data set contains the dual solution to the QP model. Information about the objective rows of the QP problems is not included. The variables in the data set have the following names and meanings.
- _OBJ_ID_
-
specifies the name of the objective function. This is particularly useful when there are multiple objective functions, in which case each objective function has a unique name.
See "ROWS Section" for details.
Note: PROC OPTQP does not support simultaneous optimization of multiple objective functions in this release.
- _RHS_ID_
-
specifies the name of the variable containing the right-hand-side value of each constraint.
See "ROWS Section" for details.
- _ROW_
-
specifies the name of the constraint. See "ROWS Section" for details.
- _TYPE_
-
specifies the type of the constraint. _TYPE_ can take one of the following values:
- L
- "less than or equals" constraint
- E
- equality constraint
- G
- "greater than or equals" constraint
- R
- ranged constraint (both "less than or equals" and "greater than or equals")
See "ROWS Section" and "RANGES Section (Optional)" for details.
- _RHS_
-
specifies the value of the right-hand side of the constraints. It takes a missing value for a ranged constraint.
- _L_RHS_
-
specifies the lower bound of a ranged constraint. It takes a missing value for a non-ranged constraint.
- _U_RHS_
-
specifies the upper bound of a ranged constraint. It takes a missing value for a non-ranged constraint.
- _VALUE_
-
specifies the value of the dual variable associated with the constraint.
- _STATUS_
-
specifies the status of the constraint.
_STATUS_ can indicate one of the following two cases:
- O
- QP problem is optimal.
- I
- QP problem could be infeasible or unbounded, or PROC OPTQP was not able to solve the problem.
- _ACTIVITY_
-
specifies the value of a constraint. In other words, the value of _ACTIVITY_
for the th constraint would be equal to , where
refers to the th row of the constraints matrix and
denotes the vector of current decision variable values.
Copyright © 2008 by SAS Institute Inc., Cary, NC, USA. All rights reserved.