PROC LP

Introduction to Optimization

PROC LP

The LP procedure solves linear and mixed integer programs. 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 following diagram illustrates all the input and output data sets that are possible with PROC LP. It also shows the macro variable _ORLP_ that PROC LP defines.

$\begin{picture} (360,160) \thicklines \put(65,115){\makebox(0,0)[r]{Problem... ...t(168,10){\makebox(0,0){\_ORLP\_}} \put(168,70){\vector(0,-1){50}}\end{picture}$

Figure 1.1: Input and Output Data Sets in PROC LP

The problem data describing the model can be in one of two formats: a sparse or a dense format. The dense format represents the model as a rectangular matrix. The sparse format represents only the nonzero elements of a rectangular matrix. The sparse and dense input formats are described in more detail later in this chapter.

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