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Alternatively, If A is an adjacency matrix for the graph, modified to have nonzero entries on its main diagonal, then the nonzero entries of A k give the adjacency matrix of the k th power of the graph, [14] from which it follows that constructing k th powers may be performed in an amount of time that is within a logarithmic factor of the time ...
G(V, E): weighted directed graph, with set of vertices V and set of directed edges E, w(u, v): cost of directed edge from node u to node v (costs are non-negative). Links that do not satisfy constraints on the shortest path are removed from the graph s: the source node; t: the destination node; K: the number of shortest paths to find; p u: a ...
Graph coloring [2] [3]: GT4 Graph homomorphism problem [3]: GT52 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.
In graph theory, Yen's algorithm computes single-source K-shortest loopless paths for a graph with non-negative edge cost. [1] The algorithm was published by Jin Y. Yen in 1971 and employs any shortest path algorithm to find the best path, then proceeds to find K − 1 deviations of the best path.
In algebraic number theory the n-th power residue symbol (for an integer n > 2) is a generalization of the (quadratic) Legendre symbol to n-th powers. These symbols are used in the statement and proof of cubic , quartic , Eisenstein , and related higher [ 1 ] reciprocity laws .
When k is a fixed constant, the k-minimum spanning tree problem can be solved in polynomial time by a brute-force search algorithm that tries all k-tuples of vertices.. However, for variable k, the k-minimum spanning tree problem has been shown to be NP-hard by a reduction from the Steiner tree
In one direction, the Hamiltonian path problem for graph G can be related to the Hamiltonian cycle problem in a graph H obtained from G by adding a new universal vertex x, connecting x to all vertices of G. Thus, finding a Hamiltonian path cannot be significantly slower (in the worst case, as a function of the number of vertices) than finding a ...
The main difference between modular decomposition and power graph analysis is the emphasis of power graph analysis in decomposing graphs not only using modules of nodes but also modules of edges (cliques, bicliques). Indeed, power graph analysis can be seen as a loss-less simultaneous clustering of both nodes and edges.