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An example of a bipartite graph, with a maximum matching (blue) and minimum vertex cover (red) both of size six. In the mathematical area of graph theory, Kőnig's theorem, proved by Dénes Kőnig (), describes an equivalence between the maximum matching problem and the minimum vertex cover problem in bipartite graphs.
Example graph that has a vertex cover comprising 2 vertices (bottom), but none with fewer. In graph theory, a vertex cover (sometimes node cover) of a graph is a set of vertices that includes at least one endpoint of every edge of the graph. In computer science, the problem of finding a minimum vertex cover is a classical optimization problem.
The minimum degree of a graph is denoted by (), and is the minimum of 's vertices' degrees. In the multigraph shown on the right, the maximum degree is 5 and the minimum degree is 0. In a regular graph, every vertex has the same degree, and so we can speak of the degree of the graph.
The equation of a line is given by = +. The equation of the normal of that line which passes through the point P is given = +. The point at which these two lines intersect is the closest point on the original line to the point P. Hence:
Via this result, the minimum vertex cover, maximum independent set, and maximum vertex biclique problems may be solved in polynomial time for bipartite graphs. Hall's marriage theorem provides a characterization of bipartite graphs which have a perfect matching and the Tutte theorem provides a characterization for arbitrary graphs.
The vertex-connectivity statement of Menger's theorem is as follows: . Let G be a finite undirected graph and x and y two nonadjacent vertices. Then the size of the minimum vertex cut for x and y (the minimum number of vertices, distinct from x and y, whose removal disconnects x and y) is equal to the maximum number of pairwise internally disjoint paths from x to y.
The problem of finding a maximum vertex-packing in a graph is equivalent to the problem of finding a maximum matching in a hypergraph: [1]: 467 Given a hypergraph H = ( V , E ) , define its intersection graph Int( H ) as the simple graph whose vertices are E and whose edges are pairs ( e 1 , e 2 ) such that e 1 , e 2 have a vertex in common.
The maximum independent set and its complement, the minimum vertex cover problem, is involved in proving the computational complexity of many theoretical problems. [28] They also serve as useful models for real world optimization problems, for example maximum independent set is a useful model for discovering stable genetic components for ...