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  2. Nearest neighbor graph - Wikipedia

    en.wikipedia.org/wiki/Nearest_neighbor_graph

    The nearest neighbor graph (NNG) is a directed graph defined for a set of points in a metric space, such as the Euclidean distance in the plane. The NNG has a vertex for each point, and a directed edge from p to q whenever q is a nearest neighbor of p, a point whose distance from p is minimum among all the given points other than p itself. [1]

  3. Nearest neighbour algorithm - Wikipedia

    en.wikipedia.org/wiki/Nearest_neighbour_algorithm

    If all the vertices in the domain are visited, then terminate. Else, go to step 3. The sequence of the visited vertices is the output of the algorithm. The nearest neighbour algorithm is easy to implement and executes quickly, but it can sometimes miss shorter routes which are easily noticed with human insight, due to its "greedy" nature.

  4. Distance (graph theory) - Wikipedia

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

    The latter may occur even if the distance in the other direction between the same two vertices is defined. In the mathematical field of graph theory, the distance between two vertices in a graph is the number of edges in a shortest path (also called a graph geodesic) connecting them. This is also known as the geodesic distance or shortest-path ...

  5. 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.

  6. Dijkstra's algorithm - Wikipedia

    en.wikipedia.org/wiki/Dijkstra's_algorithm

    1 function Dijkstra(Graph, source): 2 3 for each vertex v in Graph.Vertices: 4 dist[v] ← INFINITY 5 prev[v] ← UNDEFINED 6 add v to Q 7 dist[source] ← 0 8 9 while Q is not empty: 10 u ← vertex in Q with minimum dist[u] 11 remove u from Q 12 13 for each neighbor v of u still in Q: 14 alt ← dist[u] + Graph.Edges(u, v) 15 if alt < dist[v ...

  7. Metric k-center - Wikipedia

    en.wikipedia.org/wiki/Metric_k-center

    In graph theory, this means finding a set of k vertices for which the largest distance of any point to its closest vertex in the k-set is minimum. The vertices must be in a metric space, providing a complete graph that satisfies the triangle inequality. It has application in facility location and clustering. [1] [2]

  8. Distance matrix - Wikipedia

    en.wikipedia.org/wiki/Distance_matrix

    The geometric-distance matrix is a different type of distance matrix that is based on the graph-theoretical distance matrix of a molecule to represent and graph the 3-D molecule structure. [8] The geometric-distance matrix of a molecular structure G is a real symmetric n x n matrix defined in the same way as a 2-D matrix.

  9. Neighbourhood (graph theory) - Wikipedia

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

    The neighbourhood of a vertex v in a graph G is the subgraph of G induced by all vertices adjacent to v, i.e., the graph composed of the vertices adjacent to v and all edges connecting vertices adjacent to v. The neighbourhood is often denoted ⁠ ⁠ or (when the graph is unambiguous) ⁠ ⁠. The same neighbourhood notation may also be used ...