The OPTNET Procedure

ODS Table Names

Each table that the OPTNET procedure creates has a name associated with it, and you must use this name to refer to the table when you use ODS statements. These names are listed in Table 2.34.

Table 2.34: ODS Tables Produced by PROC OPTNET

Table Name	Description	Required Statement or Option
PerformanceInfo	Information about the computing environment	Default output
ProblemSummary	Summary of the graph (or matrix) input	Default output
SolutionSummary	For each algorithm, summary of the solution status	Default output
Timing	Detailed real times for each phase of the procedure	PERFORMANCE with DETAILS option

The following code uses the example in the section Traveling Salesman Problem Applied to a Simple Undirected Graph and calculates both an optimal traveling salesman tour and a minimum spanning tree. This code produces all four ODS output tables listed in Table 2.34.

data LinkSetIn;
   input from $ to $ weight @@;
   datalines;
A B 1.0 A C 1.0 A D 1.5 B C 2.0 B D 4.0
B E 3.0 C D 3.0 C F 3.0 C H 4.0 D E 1.5
D F 3.0 D G 4.0 E F 1.0 E G 1.0 F G 2.0
F H 4.0 H I 3.0 I J 1.0 C J 5.0 F J 3.0
F I 1.0 H J 1.0
;

proc optnet
   loglevel   = moderate
   data_links = LinkSetIn
   out_nodes  = NodeSetOut;
   mst
     out      = MST;
   tsp
     out      = TSP;
run;
%put &_OROPTNET_;
%put &_OROPTNET_TSP_;
%put &_OROPTNET_MST_;

The problem summary table in Figure 2.79 provides a basic summary of the graph (or matrix) input.

Figure 2.79: Problem Summary Table

The OPTNET Procedure

Problem Summary
Input Type	Graph
Number of Nodes	10
Number of Links	22
Graph Direction	Undirected

The solution summary tables in Figure 2.80 and Figure 2.81 provide a basic solution summary for each algorithm that is processed. The information in these tables matches the information that is provided in the macro variables for each algorithm, described in the section Macro Variables.

Figure 2.80: Solution Summary Table for MST

Solution Summary
Problem Type	Minimum Spanning Tree
Solution Status	Optimal
Objective Value	10
CPU Time	0.00
Real Time	0.00

Figure 2.81: Solution Summary Table for TSP

Solution Summary
Problem Type	Traveling Salesman Problem
Solution Status	Optimal
Objective Value	16
Relative Gap	0
Absolute Gap	0
Primal Infeasibility	0
Bound Infeasibility	0
Integer Infeasibility	0
Best Bound	16
Nodes	1
Iterations	17
CPU Time	0.00
Real Time	0.01