The maximum clique problem is the special case in which all weights are one.

An example of a problem where this method has been used is the Clique problem.

For example, the maximum clique problem arises in the following real-world setting.

A clique problem for a class of so-called M-graphs.

For example, the results related to the clique problem have the following corollaries:

However, for this variant of the clique problem better worst-case time bounds are possible.

Finding the largest complete graph is called the clique problem (NP-complete).

The clique problem may be exacerbated by the influx of former New York City officers.

The computational difficulty of the clique problem has led it to be used to prove several lower bounds in circuit complexity.

Karp originally showed set packing NP-complete via a reduction from the clique problem.

This problem is known to be NP-Hard by a reduction from the clique problem.

Covering problems are specific instances of subgraph-finding problems, and they tend to be closely related to the clique problem or the independent set problem.

Therefore, longest increasing subsequence algorithms can be used to solve the clique problem efficiently in permutation graphs.

Clique problems include:

Since the work of Harary and Ross, many others have devised algorithms for various versions of the clique problem.

In computational complexity theory, the 'clique problem' is a graph theory NP-complete problem.

Along with its applications in social networks, the clique problem also has many applications in bioinformatics and computational chemistry.

An accurate polynomial-time approximation to the clique problem would allow these two sets of graphs to be distinguished from each other, and is therefore also impossible.

Then, the clique problem is the problem of determining whether a graph contains a clique of at least a given size 'k'.

Together with Joep Kerbosch he invented the Bron-Kerbosch algorithm for the clique problem.

Contains the TSP and Max Clique problems.

In computer science, the clique problem is the computational problem of finding a maximum clique, or all cliques, in a given graph.

NP-completeness can be proven by reduction from 3-satisfiability or, as Karp did, by reduction from the clique problem.

In the complement graphs of bipartite graphs, König's theorem allows the maximum clique problem to be solved using techniques for matching.

There is an algorithm for maximum weighted independent set problem and an algorithm for the maximum weighted clique problem.