A circular layout may be used on its own for an entire graph drawing, but it also may be used as the layout for smaller clusters of vertices within a larger graph drawing, such as its biconnected components, clusters of genes in a gene interaction graph, or natural subgroups within a social network. If multiple vertex circles are used in this way, other methods such as force-directed graph drawing may be used to arrange the clusters.
The visual distinction between the inside and the outside of the vertex circle in a circular layout may be used to separate two different styles of edge drawing. For instance, a circular drawing algorithm of Gansner & Koren (2007) uses edge bundling within the circle, together with some edges that are not bundled, drawn outside the circle.
Heuristic methods for reducing the crossing complexity have also been devised, based e.g. on a careful vertex insertion order and on local optimization. A circular layout may also be used to maximize the number of crossings. In particular, choosing a random permutation for the vertices causes each possible crossing to occur with probability 1/3, so the expected number of crossings is within a factor of three of the maximum number of crossings among all possible layouts. Derandomizing this method gives a deterministic approximation algorithm with approximation ratio three.
Along with crossings, circular versions of problems of optimizing the lengths of edges in a circular layout, the angular resolution of the crossings, or the cutwidth (the maximum number of edges that connects one arc of the circle to the opposite arc) have also been considered, but many of these problems are NP-complete.
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