PROC OPTLP: Example 15.2: Using the Interior Point Solver :: SAS/OR(R) 9.2 User's Guide: Mathematical Programming

The OPTLP Procedure

Example 15.2: Using the Interior Point Solver

You can also solve the oil refinery problem described in Example 15.1 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 the section "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 15.2.1.

Output 15.2.1: Interior Point Solver: Primal Solution Output

The OPTLP Procedure

Primal Solution

Obs	Objective Function ID	Variable Name	Variable Type	Objective Coefficient	Upper Bound	Variable Value	Reduced Cost
1	profit	a_l	D	-175	110	110.000	.
2	profit	a_h	D	-165	165	0.000	.
3	profit	br	D	-205	80	80.000	.
4	profit	na_l	N	0	1.7977E308	7.450	.
5	profit	na_i	N	0	1.7977E308	21.800	.
6	profit	h_o	N	0	1.7977E308	77.300	.
7	profit	j_1	N	350	1.7977E308	72.667	.
8	profit	j_2	N	350	1.7977E308	33.042	.

The iteration log is displayed in Output 15.2.2.

Output 15.2.2: Log: Solution Progress


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 34958 384.219096 0 0 0
1 2673.363162 29.592780 0 0 0
2 277.996721 5.028437 0 0 0
3 105.556374 3.304951 0 0 0
4 11.839657 5.102811 0 0 0
5 4.437942 0.286014 0 0 0
6 0.315096 0.030434 0 0 0
7 0.017297 0.001519 0 0 0
8 0.000402 0.000075869 0 0 0
9 0.000018868 0.000003793 0 0 0
10 0.000000940 0.000000190 0 0 0
NOTE: Optimal.
NOTE: Objective = 1347.91648.

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