Vertex cycle cover

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File:Cycle cover.svg
The top graph is vertex covered by 3 cycles, and the cycles share both vertices (vertex 3) and edges (edge between 4 and 6).

The middle graph is covered by 2 cycles, and while there is a vertex overlap (vertex 3), no edges are used twice, making the covering an edge-disjoint.

The bottom graph has a covering where no vertex or edge is shared between the cycles, making the covering both edge-disjoint and vertex-disjoint.

In mathematics, a vertex cycle cover (commonly called simply cycle cover) of a graph G is a set of cycles which are subgraphs of G and contain all vertices of G.

If the cycles of the cover have no vertices in common, the cover is called vertex-disjoint or sometimes simply disjoint cycle cover. This is sometimes known as exact vertex cycle cover. In this case the set of the cycles constitutes a spanning subgraph of G. A disjoint cycle cover of an undirected graph (if it exists) can be found in polynomial time by transforming the problem into a problem of finding a perfect matching in a larger graph.[1][2]

If the cycles of the cover have no edges in common, the cover is called edge-disjoint or simply disjoint cycle cover.

Similar definitions exist for digraphs, in terms of directed cycles. Finding a vertex-disjoint cycle cover of a directed graph can also be performed in polynomial time by a similar reduction to perfect matching.[3] However, adding the condition that each cycle should have length at least 3 makes the problem NP-hard.[4]

Properties and applications

Permanent

The permanent of a (0,1)-matrix is equal to the number of vertex-disjoint cycle covers of a directed graph with this adjacency matrix. This fact is used in a simplified proof showing that computing the permanent is #P-complete.[5]

Minimal disjoint cycle covers

The problems of finding a vertex disjoint and edge disjoint cycle covers with minimal number of cycles are NP-complete. The problems are not in complexity class APX. The variants for digraphs are not in APX either.[6]

See also

References

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  3. https://www.cs.cmu.edu/~avrim/451f13/recitation/rec1016.txt (problem 1)
  4. Garey and Johnson, Computers and intractability, GT13
  5. Ben-Dor, Amir and Halevi, Shai. (1993). "Zero-one permanent is #P-complete, a simpler proof". Proceedings of the 2nd Israel Symposium on the Theory and Computing Systems, 108-117.
  6. Complexity and Approximation: Combinatorial Optimization Problems and Their Approximability Properties (1999) Template:ISBN p.378, 379, citing Script error: No such module "citation/CS1"..

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