The LP Procedure
- Overview
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Getting Started
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Syntax
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Details
Missing Values Dense Data Input Format Sparse Data Input Format Converting Any PROC LP Format to an MPS-Format SAS Data Set Converting Standard MPS Format to Sparse Format The Reduced Costs, Dual Activities, and Current Tableau Macro Variable ORLP Pricing Scaling Preprocessing Integer Programming Sensitivity Analysis Range Analysis Parametric Programming Interactive Facilities Memory Management Output Data Sets Input Data Sets Displayed Output ODS Table and Variable Names Memory Limit
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Examples
An Oil Blending Problem A Sparse View of the Oil Blending Problem Sensitivity Analysis: Changes in Objective Coefficients Additional Sensitivity Analysis Price Parametric Programming for the Oil Blending Problem Special Ordered Sets and the Oil Blending Problem Goal-Programming a Product Mix Problem A Simple Integer Program An Infeasible Problem Restarting an Integer Program Alternative Search of the Branch-and-Bound Tree An Assignment Problem A Scheduling Problem A Multicommodity Transshipment Problem with Fixed Charges Converting to an MPS-Format SAS Data Set Migration to OPTMODEL: Assignment Migration to OPTMODEL: Multicommodity Transshipment
- References
| Scaling |
Based on the SCALE= option specified, the procedure scales the coefficients of both the constraints and objective rows before iterating. This technique can improve the numerical stability of an ill-conditioned problem. If you want to modify the default matrix scaling used, which is SCALE=BOTH, use the SCALE=COLUMN, SCALE=ROW, or SCALE=NONE option in the PROC LP statement. If SCALE=BOTH, the matrix coefficients are scaled so that the largest element in absolute value in each row or column equals 1. They are scaled by columns first and then by rows. If SCALE=COLUMN (ROW), the matrix coefficients are scaled so that the largest element in absolute value in each column (row) equals 1. If SCALE=NONE, no scaling is performed.