The OPTLP Procedure
Getting Started: OPTLP Procedure
The following example illustrates how you can use the OPTLP procedure to solve linear programs. Suppose you want to solve the following problem:
The corresponding MPS-format SAS data set is as follows:
data example;
input field1 $ field2 $ field3 $ field4 field5 $ field6;
datalines;
NAME . EXAMPLE . . .
ROWS . . . . .
N COST . . . .
G R1 . . . .
L R2 . . . .
L R3 . . . .
COLUMNS . . . . .
. X1 COST 2 R2 1
. X1 R3 1 . .
. X2 COST -3 R1 -2
. X2 R2 1 R3 2
. X3 COST -4 R1 -3
. X3 R2 2 R3 3
RHS . . . . .
. RHS R1 -5 R2 4
. RHS R3 7 . .
ENDATA . . . . .
;
You can also create this data set from an MPS-format flat file (examp.mps) by using the following SAS macro:
%mps2sasd(mpsfile = "examp.mps", outdata = example);
Note: The SAS macro %MPS2SASD is provided in SAS Optimization software. See Converting an MPS/QPS-Format File: %MPS2SASD for details.
To make the created data set available on the CAS server, you need to upload it as in the following statements. At the same time, you also add an _id_ column to ensure that the MPS reader can read the file in the correct order even if it is distributed across several machines and hence loses the original ordering. For more information about the MPS-format, see Chapter 8, The MPS-Format Data Table.
data mylib.example;
set example;
_id_ = _n_;
run;
Alternatively, you can create the MPS data table directly in CAS and include the _id_ column in the datalines input.
You can use the following statement to call the OPTLP procedure:
title1 'The OPTLP Procedure';
proc optlp data = mylib.example
objsense = min
presolver = automatic
algorithm = primal
primalout = mylib.expout
dualout = mylib.exdout;
run;
Note: The "N" designation for "COST" in the rows section of the data table example also specifies a minimization problem. See the section ROWS Section for details.
The optimal primal and dual solutions are stored in the data tables expout and exdout, respectively, and are displayed in Figure 1.
title2 'Primal Solution';
proc print data=mylib.expout label;
run;
title2 'Dual Solution';
proc print data=mylib.exdout label;
run;
Figure 1: Primal and Dual Solution Output
| The OPTLP Procedure |
| Primal Solution |
| Obs | Objective Function ID | RHS ID | Variable Name | Variable Type | Objective Coefficient | Lower Bound | Upper Bound | Variable Value | Variable Status | Reduced Cost |
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | COST | RHS | X1 | N | 2 | 0 | 1.7977E308 | 0.0 | L | 2.0 |
| 2 | COST | RHS | X2 | N | -3 | 0 | 1.7977E308 | 2.5 | B | 0.0 |
| 3 | COST | RHS | X3 | N | -4 | 0 | 1.7977E308 | 0.0 | L | 0.5 |
| The OPTLP Procedure |
| Dual Solution |
| Obs | Objective Function ID | RHS ID | Constraint Name | Constraint Type | Constraint RHS | Constraint Lower Bound | Constraint Upper Bound | Dual Solution | Constraint Status | Constraint Activity |
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | COST | RHS | R1 | G | -5 | . | . | 1.5 | U | -5.0 |
| 2 | COST | RHS | R2 | L | 4 | . | . | 0.0 | B | 2.5 |
| 3 | COST | RHS | R3 | L | 7 | . | . | 0.0 | B | 5.0 |
For details about the type and status codes displayed for variables and constraints, see the section Data Input and Output.