A connected component of a graph is a set of nodes that are all reachable from each other. That is, if two nodes are in the same component, then there exists a path between them. For a directed graph, there are two types of components: a strongly connected component has a directed path between any two nodes, and a weakly connected component ignores direction and requires only that a path exists between any two nodes.
In the network solver, you can invoke connected components by using the CONCOMP= option.
The default algorithm for finding connected components is a depth-first search. For undirected graphs only, you can also specify ALGORITHM= UNION_FIND. Given a graph , both algorithms run in time and can usually scale to very large graphs, but sometimes the union-find algorithm can be faster.
The results for the connected components algorithm are written to the node-indexed numeric array that is specified in the CONCOMP= suboption of the OUT= option. For each node in the set, the value of this array identifies its component. The component identifiers are numbered sequentially starting from 1.
This section illustrates the use of the connected components algorithm on the simple undirected graph G that is shown in Figure 9.23.
The undirected graph G can be represented by the following links data set LinkSetIn
:
data LinkSetIn; input from $ to $ @@; datalines; A B A C B C C H D E D F D G F E G I K L ;
The following statements calculate the connected components and output the results in the data set NodeSetOut
:
proc optmodel; set<str,str> LINKS; read data LinkSetIn into LINKS=[from to]; set NODES = union {<i,j> in LINKS} {i,j}; num component{NODES}; solve with NETWORK / links = (include=LINKS) concomp out = (concomp=component) ; print component; create data NodeSetOut from [node] concomp=component; quit;
The data set NodeSetOut
contains the connected components of the input graph and is shown in Figure 9.24.
Notice that the graph was defined by using only the links array. As seen in Figure 9.23, this graph also contains a singleton node labeled J, which has no associated links. By definition, this node defines its
own component. But because the input graph was defined by using only the links array, it did not show up in the results data
set. To define a graph by using nodes that have no associated links, you should also define the input nodes data set. In this
case, define the nodes data set NodeSetIn
as follows:
data NodeSetIn; input node $ @@; datalines; A B C D E F G H I J K L ;
Now, when you calculate the connected components, you define the input graph by using both the nodes input data set and the links input data set:
proc optmodel; set<str,str> LINKS; read data LinkSetIn into LINKS=[from to]; set<str> NODES; read data NodeSetIn into NODES=[node]; num component{NODES}; solve with NETWORK / links = (include=LINKS) nodes = (include=NODES) concomp out = (concomp=component) ; print component; create data NodeSetOut from [node] concomp=component; quit;
The resulting data set, NodeSetOut
, includes the singleton node J as its own component, as shown in Figure 9.25.
This section illustrates the use of the connected components algorithm on the simple directed graph G that is shown in Figure 9.26.
The directed graph G can be represented by the following links data set LinkSetIn
:
data LinkSetIn; input from $ to $ @@; datalines; A B B C B E B F C G C D D C D H E A E F F G G F H G H D ;
The following statements calculate the connected components and output the results in the data set NodeSetOut
:
proc optmodel; set<str,str> LINKS; read data LinkSetIn into LINKS=[from to]; set NODES = union {<i,j> in LINKS} {i,j}; num component{NODES}; solve with NETWORK / graph_direction = directed links = (include=LINKS) concomp out = (concomp=component) ; print component; create data NodeSetOut from [node] concomp=component; quit;
The data set NodeSetOut
, shown in Figure 9.27, now contains the connected components of the input graph.
The connected components are represented graphically in Figure 9.28.