Examples of using Maximum clique in English and their translations into Russian
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Find the size of the maximum clique in such graph.
In this case, I∪{x} is a maximum independent set and C is a maximum clique.
In this case, C∪{x}is a maximum clique and I is a maximum independent set.
Print a single number- the number of vertexes in the maximum clique of the given graph.
For a node labeled 0, the maximum clique is the maximum among the cliques computed for that node's children.
A tree has treewidth one by the same reasoning as for complete graphs namely, it is chordal,and has maximum clique size two.
If the doubled vertex belongs to a maximum clique of the graph, it increases both the clique number and the chromatic number by one.
In computer science, the clique problem is the computational problem of finding a maximum clique, or all cliques, in a given graph.
The removed vertices meet every maximum clique, so H has clique number and chromatic number one less than that of the given graph.
Others are impossible to approximate within any constant, or even polynomial,factor unless P NP, as in the case of the Maximum Clique Problem.
A perfect graph is a graph in which the chromatic number and the size of the maximum clique are equal, and in which this equality persists in every induced subgraph.
For instance, to find the maximum clique in a cograph, compute in bottom-up order the maximum clique in each subgraph represented by a subtree of the cotree.
Many of the known lower bounds on Ramsey numbers come from examples of circulant graphs that have small maximum cliques and small maximum independent sets.
For a node labeled 1, the maximum clique is the union of the cliques computed for that node's children, and has size equal to the sum of the children's clique sizes.
In this case, G has a unique partition(C, I) into a clique and an independent set,C is the maximum clique, and I is the maximum independent set.
Corrádi and Szabó showed that the maximum clique in this graph has size at most 2n, and that if there is a clique of this size then Keller's conjecture is false.
Let G be a split graph, partitioned into a clique C and an independent set I. Then every maximal clique in a split graph is either C itself, or the neighborhood of avertex in I. Thus, it is easy to identify the maximum clique, and complementarily the maximum independent set in a split graph.
For instance, in all perfect graphs, the graph coloring problem, maximum clique problem, and maximum independent set problem can all be solved in polynomial time.
See in particular pp. 21:"Maximum clique(and therefore also maximum independent set and maximum set packing) cannot be approximated to within O( n 1- ϵ){\displaystyle O(n^{1-\epsilon})} unless NP⊂ ZPP.
For the perfect graphs,a number of NP-complete optimization problems(graph coloring problem, maximum clique problem, and maximum independent set problem) are polynomially solvable.
The largest maximal clique is a maximum clique, and, as chordal graphs are perfect, the size of this clique equals the chromatic number of the chordal graph.
Thus, by alternately maximizing and summing values stored at each node of the cotree,we may compute the maximum clique size, and by alternately maximizing and taking unions, we may construct the maximum clique itself.
Thus, it is possible in polynomial time to find the maximum clique or maximum independent set in a distance-hereditary graph, or to find an optimal graph coloring of any distance-hereditary graph.
Pathwidth is also known as interval thickness(one less than the maximum clique size in an interval supergraph of G), vertex separation number, or node searching number.
Despite the close relationship between maximum cliques and maximum independent sets in arbitrary graphs, the independent set and clique problems may be very different when restricted to special classes of graphs.
Using(k- 1)-dimensional range trees to store andquery coordinates, Felsner's algorithms for chromatic number, maximum clique, and maximum independent set can be applied to k-trapezoid graphs in O( n log k- 1 n){\displaystyle{O}(n\log^{k-1}n)} time.
Thus, perfection(defined as the equality of maximum clique size and chromatic number in every induced subgraph) is equivalent to the equality of maximum independent set size and clique cover number.
In contrast, for random graphs in the Erdős-Rényi model with edge probability 1/2, both the maximum clique and the maximum independent set are much smaller: their size is proportional to the logarithm of n{\displaystyle n}, rather than growing polynomially.
If, on the other hand, the doubled vertex does not belong to a maximum clique, form a graph H by removing the vertices with the same color as the doubled vertex(but not the doubled vertex itself) from an optimal coloring of the given graph.
In all perfect graphs,the graph coloring problem, maximum clique problem, and maximum independent set problem can all be solved in polynomial time Grötschel, Lovász& Schrijver 1988.