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/OR software. See the section "Converting an MPS/QPS-Format File: %MPS2SASD" for details.

You can use the following statement to call the OPTLP procedure:

    proc optlp data = example
      objsense  = min
      presolver = automatic 
      solver    = primal
      primalout = expout 
      dualout   = exdout; 
    run;
 

Note: The "N" designation for "COST" in the rows section of the data set example also specifies a minimization problem. See the section "ROWS Section" for details.

The optimal primal and dual solutions are stored in the data sets expout and exdout, respectively, and are displayed in Figure 15.1.

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 Variable Value 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

Figure 15.1: Primal and Dual Solution Output

For details about the type and status codes displayed for variables and constraints, see the section "Data Input and Output".