Chapter Contents |
Previous |
Next |

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.

Chapter Contents |
Previous |
Next |
Top |

Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.