The OPTMILP Procedure
| Data Input and Output |
This subsection describes the PRIMALIN= data set required to warm start PROC OPTMILP, in addition to the PRIMALOUT= and DUALOUT= data sets.
Definitions of Variables in the PRIMALIN= Data Set
The PRIMALIN= data set has two required variables defined as follows:
Note: If PROC OPTMILP produces a feasible solution, the primal output data set from that run can be used as the PRIMALIN= data set for a subsequent run, provided that the variable names are the same. If this input solution is not feasible for the subsequent run, the solver automatically tries to repair it. See the section Warm Start for more details.
Definitions of Variables in the PRIMALOUT= Data Set
PROC OPTMILP stores the current best integer feasible solution of the problem in the data set specified by the PRIMALOUT= option. The variables in this data set are defined as follows:
- _OBJ_ID_
- _RHS_ID_
- _VAR_
- _TYPE_
-
specifies the variable type. _TYPE_ can take one of the following values:
- C
continuous variable
- I
general integer variable
- B
binary variable (0 or 1)
- _OBJCOEF_
specifies the coefficient of the variable in the objective function.
- _LBOUND_
- _UBOUND_
- _VALUE_
specifies the value of the variable in the current solution.
Definitions of the DUALOUT= Data Set Variables
The DUALOUT= data set contains the constraint activities that correspond to the primal solution in the PRIMALOUT= data set. Information about additional objective rows of the MILP problem is not included. The variables in this data set are defined as follows:
- _OBJ_ID_
specifies the identifier of the objective function from the input data set.
- _RHS_ID_
specifies the identifier of the right-hand side from the input data set.
- _ROW_
- _TYPE_
-
specifies the constraint type. _TYPE_ can take one of the following values:
- L
"less than or equal" constraint
- E
equality constraint
- G
"greater than or equal" constraint
- R
ranged constraint (both "less than or equal" and "greater than or equal")
- _RHS_
specifies the value of the right-hand side of the constraint. 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.
- _ACTIVITY_
specifies the activity of a constraint for a given primal solution. In other words, the value of _ACTIVITY_ for the
th constraint is equal to 
, where 
refers to the th row of the constraint matrix and 
denotes the vector of the current primal solution.
Data Magnitude and Variable Bounds
Extremely large numerical values might cause computational difficulties for the OPTMILP procedure, but the occurrence of such difficulties is hard to predict. For this reason, the OPTMILP procedure issues a data error message whenever it detects model data that exceeds a specific threshold number. The value of the threshold number depends on your operating environment and is printed in the log as part of the data error message.
The following conditions produce a data error:
The absolute value of an objective coefficient, constraint coefficient, or range (difference between the upper and lower bounds on a constraint) is greater than the threshold number.
A variable’s lower bound, the right-hand side of a
or 
constraint, or a range constraint’s lower bound is greater than the threshold number. A variable’s upper bound, the right-hand side of a
or constraint, or a range constraint’s upper bound is smaller than the negative threshold number.
If a variable’s upper bound is larger than 1E20, then the OPTMILP procedure treats the bound as 
. Similarly, if a variable’s lower bound is smaller than –1E20, then the OPTMILP procedure treats the bound as 
.