The LP procedure solves linear and mixed integer programs with a primal simplex solver. It can perform several types of post-optimality analysis, including range analysis, sensitivity analysis, and parametric programming. The procedure can also be used interactively.

PROC LP requires a problem data set that contains the model. In addition, a primal and active data set can be used for warm starting a problem that has been partially solved previously.

The problem data describing the model can be in one of two formats: dense or sparse. The dense format represents the model as a rectangular coefficient matrix. The sparse format, on the other hand, represents only the nonzero elements of a rectangular coefficient matrix.

For more details on the LP procedure, refer to Chapter 5, The LP Procedure.

Problem data specified in the format used by the LP procedure can be readily reformatted for use with the newer OPTLP procedure. The MPSOUT= option in the LP procedure enables you to convert data in the format used by the LP procedure into an MPS-format SAS data set for use with the OPTLP procedure. For more information about the OPTLP procedure, see Chapter 17, The OPTLP Procedure. For more information about the MPS-format SAS data set, see Chapter 16, The MPS-Format SAS Data Set.