The OPTNET Procedure
- Overview
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Getting Started
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SyntaxFunctional SummaryPROC OPTNET StatementBICONCOMP StatementCLIQUE StatementCONCOMP StatementCYCLE StatementDATA_LINKS_VAR StatementDATA_MATRIX_VAR StatementDATA_NODES_VAR StatementLINEAR_ASSIGNMENT StatementMINCOSTFLOW StatementMINCUT StatementMINSPANTREE StatementSHORTPATH StatementTRANSITIVE_CLOSURE StatementTSP Statement
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DetailsGraph Input DataMatrix Input DataNumeric LimitationsSize LimitationsBiconnected Components and Articulation PointsCliqueConnected ComponentsCycleLinear Assignment (Matching)Minimum-Cost Network FlowMinimum CutMinimum Spanning TreeShortest PathTransitive ClosureTraveling Salesman ProblemMacro VariablesODS Table Names
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ExamplesArticulation Points in a Terrorist NetworkCycle Detection for Kidney Donor ExchangeLinear Assignment Problem for Minimizing Swim TimesLinear Assignment Problem, Sparse Format versus Dense FormatMinimum Spanning Tree for Computer Network TopologyTransitive Closure for Identification of Circular Dependencies in a Bug Tracking SystemTraveling Salesman Tour through US Capital Cities
- References
PROC OPTNET can handle any graph whose number of nodes and links are less than or equal to 2,147,483,647 (the maximum that can be represented by a 32-bit integer). This maximum also applies to 64-bit systems. For graphs of two billion nodes (or links), memory limitations also become a limiting factor.
If the data from your problem require a graph with more than two billion nodes (or links), there is typically a heuristic way to break the network into smaller networks based on problem-specific attributes. Then, using DATA steps, you can process each of the smaller networks iteratively through repeated calls to PROC OPTNET. By using DATA steps, you can also often work around memory limitations, because the full graph exists only on the disk and never resides in-memory.