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
Examples: LP Procedure
- 4.1 An Oil Blending Problem
- 4.2 A Sparse View of the Oil Blending Problem
- 4.3 Sensitivity Analysis: Changes in Objective Coefficients
- 4.4 Additional Sensitivity Analysis
- 4.5 Price Parametric Programming for the Oil Blending Problem
- 4.6 Special Ordered Sets and the Oil Blending Problem
- 4.7 Goal-Programming a Product Mix Problem
- 4.8 A Simple Integer Program
- 4.9 An Infeasible Problem
- 4.10 Restarting an Integer Program
- 4.11 Alternative Search of the Branch-and-Bound Tree
- 4.12 An Assignment Problem
- 4.13 A Scheduling Problem
- 4.14 A Multicommodity Transshipment Problem with Fixed Charges
- 4.15 Converting to an MPS-Format SAS Data Set
- 4.16 Migration to OPTMODEL: Assignment
- 4.17 Migration to OPTMODEL: Multicommodity Transshipment
The following examples illustrate some of the capabilities of PROC LP. These examples, together with the other SAS/OR examples, can be found in the SAS sample library. A description of the features of PROC LP as shown in the examples are
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Example 4.1 shows dense input format.
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Example 4.2 shows sparse input format.
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Example 4.3 uses the RANGEPRICE option to show you the range over which each objective coefficient can vary without changing the variables in the basis.
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Example 4.4 shows more sensitivity analysis and restarting a problem.
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Example 4.5 shows parametric programming.
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Example 4.6 shows special ordered sets.
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Example 4.7 shows goal programming.
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Example 4.8 shows integer programming.
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Example 4.9 shows an infeasible problem.
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Example 4.10 shows restarting integer programs.
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Example 4.11 controls the search of the branch-and-bound tree.
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Example 4.12 shows matrix generation and report writing for an assignment problem.
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Example 4.13 shows matrix generation and report writing for a scheduling problem.
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Example 4.14 shows a multicommodity transshipment problem.
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Example 4.15 shows migration to PROC OPTLP via the MPSOUT= option.
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Example 4.16 shows migration to PROC OPTMODEL.
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Example 4.17 shows migration to PROC OPTMODEL.