When.com Web Search

Search results

  1. Results From The WOW.Com Content Network
  2. Dijkstra's algorithm - Wikipedia

    en.wikipedia.org/wiki/Dijkstra's_algorithm

    Find the path of minimum total length between two given nodes P and Q. We use the fact that, if R is a node on the minimal path from P to Q, knowledge of the latter implies the knowledge of the minimal path from P to R. is a paraphrasing of Bellman's Principle of Optimality in the context of the shortest path problem.

  3. Longest path problem - Wikipedia

    en.wikipedia.org/wiki/Longest_path_problem

    In graph theory and theoretical computer science, the longest path problem is the problem of finding a simple path of maximum length in a given graph.A path is called simple if it does not have any repeated vertices; the length of a path may either be measured by its number of edges, or (in weighted graphs) by the sum of the weights of its edges.

  4. Distance (graph theory) - Wikipedia

    en.wikipedia.org/wiki/Distance_(graph_theory)

    A level structure of the graph, given a starting vertex, is a partition of the graph's vertices into subsets by their distances from the starting vertex. A geodetic graph is one for which every pair of vertices has a unique shortest path connecting them. For example, all trees are geodetic. [4]

  5. Average path length - Wikipedia

    en.wikipedia.org/wiki/Average_path_length

    All these models had one thing in common: they all predicted very short average path length. [1] The average path length depends on the system size but does not change drastically with it. Small world network theory predicts that the average path length changes proportionally to log n, where n is the number of nodes in the network.

  6. Shortest path problem - Wikipedia

    en.wikipedia.org/wiki/Shortest_path_problem

    Shortest path (A, C, E, D, F), blue, between vertices A and F in the weighted directed graph. In graph theory, the shortest path problem is the problem of finding a path between two vertices (or nodes) in a graph such that the sum of the weights of its constituent edges is minimized.

  7. Closeness centrality - Wikipedia

    en.wikipedia.org/wiki/Closeness_centrality

    The number next to each node is the distance from that node to the square red node as measured by the length of the shortest path. The green edges illustrate one of the two shortest paths between the red square node and the red circle node. The closeness of the red square node is therefore 5/(1+1+1+2+2) = 5/7.

  8. Glossary of graph theory - Wikipedia

    en.wikipedia.org/wiki/Glossary_of_graph_theory

    Length is used to define the shortest path, girth (shortest cycle length), and longest path between two vertices in a graph. level 1. This is the depth of a node plus 1, although some [12] define it instead to be synonym of depth. A node's level in a rooted tree is the number of nodes in the path from the root to the node.

  9. Distance matrix - Wikipedia

    en.wikipedia.org/wiki/Distance_matrix

    In general, a distance matrix is a weighted adjacency matrix of some graph. In a network, a directed graph with weights assigned to the arcs, the distance between two nodes of the network can be defined as the minimum of the sums of the weights on the shortest paths joining the two nodes (where the number of steps in the path is bounded). [2]