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The input to the algorithm is an undirected graph G = (V, E) with vertex set V, edge set E, and (optionally) numerical weights on the edges in E.The goal of the algorithm is to partition V into two disjoint subsets A and B of equal (or nearly equal) size, in a way that minimizes the sum T of the weights of the subset of edges that cross from A to B.
The example in Figure 3 illustrates 2 instances of the same graph such that in (a) modularity (Q) is the partitioning metric and in (b), ratio-cut is the partitioning metric. Figure 3: Weighted graph G may be partitioned to maximize Q in (a) or to minimize the ratio-cut in (b).
Graph partition into subgraphs of specific types (triangles, isomorphic subgraphs, Hamiltonian subgraphs, forests, perfect matchings) are known NP-complete. Partition into cliques is the same problem as coloring the complement of the given graph. A related problem is to find a partition that is optimal terms of the number of edges between parts ...
Therefore, in triangle-free graphs, the minimum clique cover can be found by using an algorithm for maximum matching. The optimum partition into cliques can also be found in polynomial time for graphs of bounded clique-width. [3] These include, among other graphs, the cographs and distance-hereditary graphs, which are also classes of perfect ...
These graphs are described by notation with a capital letter K subscripted by a sequence of the sizes of each set in the partition. For instance, K 2,2,2 is the complete tripartite graph of a regular octahedron , which can be partitioned into three independent sets each consisting of two opposite vertices.
An example of a maximum cut. In a graph, a maximum cut is a cut whose size is at least the size of any other cut. That is, it is a partition of the graph's vertices into two complementary sets S and T, such that the number of edges between S and T is as large as possible. Finding such a cut is known as the max-cut problem.
Given a graph , its Gallai–Edmonds decomposition consists of three disjoint sets of vertices, (), (), and (), whose union is (): the set of all vertices of .First, the vertices of are divided into essential vertices (vertices which are covered by every maximum matching in ) and inessential vertices (vertices which are left uncovered by at least one maximum matching in ).
In graph theory, a minimum cut or min-cut of a graph is a cut (a partition of the vertices of a graph into two disjoint subsets) that is minimal in some metric. Variations of the minimum cut problem consider weighted graphs, directed graphs, terminals, and partitioning the vertices into more than two sets.