The LP Procedure
- Overview
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Getting Started
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Syntax
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DetailsMissing ValuesDense Data Input FormatSparse Data Input FormatConverting Any PROC LP Format to an MPS-Format SAS Data SetConverting Standard MPS Format to Sparse FormatThe Reduced Costs, Dual Activities, and Current TableauMacro Variable _ORLP_PricingScalingPreprocessingInteger ProgrammingSensitivity AnalysisRange AnalysisParametric ProgrammingInteractive FacilitiesMemory ManagementOutput Data SetsInput Data SetsDisplayed OutputODS Table and Variable NamesMemory Limit
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ExamplesAn Oil Blending ProblemA Sparse View of the Oil Blending ProblemSensitivity Analysis: Changes in Objective CoefficientsAdditional Sensitivity AnalysisPrice Parametric Programming for the Oil Blending ProblemSpecial Ordered Sets and the Oil Blending ProblemGoal-Programming a Product Mix ProblemA Simple Integer ProgramAn Infeasible ProblemRestarting an Integer ProgramAlternative Search of the Branch-and-Bound TreeAn Assignment ProblemA Scheduling ProblemA Multicommodity Transshipment Problem with Fixed ChargesConverting to an MPS-Format SAS Data SetMigration to OPTMODEL: AssignmentMigration to OPTMODEL: Multicommodity Transshipment
- References
Syntax: LP Procedure
Below are statements used in PROC LP, listed in alphabetical order as they appear in the text that follows.
The TYPE, ID (or ROW), VAR, RHS, RHSSEN, and RANGE statements are used for identifying variables in the problem data set when
the model is in the dense input format. In the dense input format, a model’s variables appear as variables in the problem
data set. The TYPE, ID (or ROW), and RHS statements can be omitted if the input data set contains variables _TYPE_, _ID_ (or _ROW_), and _RHS_; otherwise, they must be used. The VAR statement is optional. When it is omitted, PROC LP treats all numeric variables that
are not explicitly or implicitly included in RHS, RHSSEN, and RANGE statements as structural variables. The RHSSEN and RANGE
statements are optional statements for sensitivity and range analyses. They can be omitted if the input data set contains
the _RHSSEN_ and _RANGE_ variables.
The TYPE, COL, ROW (or ID), COEF, RHS, RHSSEN, and RANGE statements are used for identifying variables in the problem data
set when the model is in the sparse input format. In the sparse input format, a model’s rows and columns appear as observations
in the problem data set. The TYPE, COL, ROW (or ID), and COEF statements can be omitted if the input data set contains the
_TYPE_ and _COL_ variables, as well as variables beginning with the prefixes _ROW (or _ID) and _COEF. Otherwise, they must be used. The RHS, RHSSEN, and RANGE statements identify the corresponding columns in the model. These
statements can be omitted if there are observations that contain the RHS, RHSSEN, and RANGE types or the _RHS_, _RHSSEN_,
and _RANGE_ column values.
The SHOW, RESET, PRINT, QUIT, PIVOT, IPIVOT, and RUN statements are especially useful when executing PROC LP interactively. However, they can also be used in batch mode.