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Introduction to Optimization |
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.
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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