 |
|
| The OPTLP Procedure |
Example 17.2 Using the Interior Point Solver
You can also solve the oil refinery problem described in Example 17.1 by using the interior point solver. You can create the input data set from an external MPS-format flat file by using the SAS macro %MPS2SASD or SAS DATA step code, both of which are described in Getting Started: OPTLP Procedure. You can use the following SAS code to solve the problem:
proc optlp data=ex1 objsense = max solver = ii primalout = ex1ipout dualout = ex1idout printfreq = 1; run;
The optimal solution is displayed in Output 17.2.1.
Output 17.2.1
Interior Point Solver: Primal 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 | profit | a_l | D | -175 | 0 | 110 | 110.000 | . | ||
| 2 | profit | a_h | D | -165 | 0 | 165 | 0.000 | . | ||
| 3 | profit | br | D | -205 | 0 | 80 | 80.000 | . | ||
| 4 | profit | na_l | N | 0 | 0 | 1.7977E308 | 7.450 | . | ||
| 5 | profit | na_i | N | 0 | 0 | 1.7977E308 | 21.800 | . | ||
| 6 | profit | h_o | N | 0 | 0 | 1.7977E308 | 77.300 | . | ||
| 7 | profit | j_1 | N | 350 | 0 | 1.7977E308 | 72.667 | . | ||
| 8 | profit | j_2 | N | 350 | 0 | 1.7977E308 | 33.042 | . |
The iteration log is displayed in Output 17.2.2.
Output 17.2.2
Log: Solution Progress
| The OPTLP Procedure |
| line |
|---|
| NOTE: The problem EX1 has 8 variables (0 free, 0 fixed). |
| NOTE: The problem has 6 constraints (3 LE, 3 EQ, 0 GE, 0 range). |
| NOTE: The problem has 19 constraint coefficients. |
| WARNING: The objective sense has been changed to maximization. |
| NOTE: The OPTLP presolver value AUTOMATIC is applied. |
| NOTE: The OPTLP presolver removed 3 variables and 3 constraints. |
| NOTE: The OPTLP presolver removed 6 constraint coefficients. |
| NOTE: The presolved problem has 5 variables, 3 constraints, and 13 constraint |
| coefficients. |
| NOTE: This is an experimental version of the ITERATIVE INTERIOR solver. |
| NOTE: The ITERATIVE INTERIOR solver is called. |
| Primal Bound Dual |
| Iter Complement Duality Gap Infeas Infeas Infeas |
| 0 45.748014 1.785339 10.241641 0.136179 0.277456 |
| 1 7.482375 2.537583 1.288997 0.017139 0.053374 |
| 2 6.321287 0.509050 1.142522 0.015192 0.050980 |
| 3 1.571932 0.127320 0.011425 0.000152 0.010973 |
| 4 1.260841 0.078028 0.008971 0.000119 0.007122 |
| 5 0.026156 0.000361 0.000101 0.000001344 0.000205 |
| 6 0.000262 0.000003629 0.000001012 1.3459193E-8 0.000002052 |
| 7 0.000002617 3.6291376E-8 1.0122347E-8 1.345919E-10 2.0517479E-8 |
| 8 0 1.701138E-15 5.644593E-15 0 1.407423E-17 |
| NOTE: Optimal. |
| NOTE: Objective = 1347.91667. |
| NOTE: The data set WORK.EX1IPOUT has 8 observations and 10 variables. |
| NOTE: The data set WORK.EX1IDOUT has 6 observations and 10 variables. |
|
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