Graph algorithms

graph search algorithm

thumb|upright=1.35|An animation of the PageRank algorithm running on a small network of pages. The size of the nodes represents the perceived importance of the page, and arrows represent hyperlinks. thumb|upright=1.35|A simple illustration of the Pagerank algorithm. The percentage shows the perceived importance, and the arrows represent hyperlinks. PageRank (PR) is an algorithm used by Google Search to rank web pages in their search engine results. It is named after both the term "web page" and co-founder Larry Page. PageRank is a way of measuring the importance of website pages. According to

algorithm for traversing or searching tree or graph data structures

NP-hard problem in combinatorial optimization

algorithm for searching the nodes of a graph in order by their hop count from a starting node

sequence of moves of a knight on a chessboard to visit each square exactly once

algorithm for finding the minimum spanning tree for weighted undirected graphs

Minimax (sometimes Minmax, MM or saddle point) is a decision rule used in artificial intelligence, decision theory, combinatorial game theory, statistics, and philosophy for minimizing the possible loss for a worst case (maximum loss) scenario. When dealing with gains, it is referred to as "maximin" – to maximize the minimum gain. Originally formulated for several-player zero-sum game theory, covering both the cases where players take alternate moves and those where they make simultaneous moves, it has also been extended to more complex games and to general decision-making in the presence of u

algorithm used for pathfinding and graph traversal

minimum spanning forest algorithm that greedily adds edges

algorithm for finding single-source shortest paths in graphs, allowing some edge weights to be negative

bijection between the vertex set of two graphs

algorithm for finding all-pairs shortest paths in graphs, allowing some edge weights to be negative

an ordering of the vertices of the directed graph for which each edge is directed from earlier to later in the ordering

algorithm

search algorithm that seeks to decrease the number of nodes that are evaluated by the minimax algorithm in its search tree

class of algorithms

algorithm for finding minimum spanning trees by repeatedly finding the shortest edge out of each subtree in a forest and adding all such edges to the forest

algorithm to find shortest paths between all pairs of vertices in a sparse, edge-weighted (possibly negatively), directed graph; uses the Bellman–Ford algorithm to remove negative weights and Dijkstra’s algorithm on the rest

algorithm

algorithm that approximates solutions to the travellng salesman problem on a metric space, guaranteeing that its solutions will be within 1½ of the optimal solution length; discovered by Nicos Christofides in 1976

operation on binary relations

algorithm for computing the maximal flow of a network

used to determine solution to travelling salesman problem

the problem of finding a simple path of maximum length in a given graph

search strategy

In graph theory and network analysis, indicators of centrality assign numbers or rankings to nodes within a graph corresponding to their network position. Applications include identifying the most influential person(s) in a social network, key infrastructure nodes in the Internet or urban networks, super-spreaders of disease, and brain networks. Centrality concepts were first developed in social network analysis, and many of the terms used to measure centrality reflect their sociological origin. Over time, the concept has expanded substantially, leading to the development of hundreds of distin

graph theory algorithm

algorithm for generating random networks

algorithm for finding shortest paths by simultaneously searching from the source and destination until both searches meet

algorithm for maximum cardinality matching in bipartite graphs

D* (pronounced "D star") is any one of the following three related incremental search algorithms:

checking and/or changing each vertex in a graph

algorithm

algorithm to find the strongly connected component of a directed graph

algorithm for finding optimal branchings in graph theory

method for picking a coordinator from distributed computer processes, in which the process with the highest ID number among non-failed processes is picked

specialized artificial neural networks that are designed for tasks whose inputs are graphs

the NP-complete problem of testing whether one graph is a subgraph of another

algorithm

algorithm

SMA* or Simplified Memory Bounded A* is a shortest path algorithm based on the A* algorithm. The main advantage of SMA* is that it uses a bounded memory, while the A* algorithm might need exponential memory. All other characteristics of SMA* are inherited from A*.

computational problem of determining whether two finite graphs are isomorphic

randomized algorithm for minimum cuts

measure of graph sparsity

physical simulation to visualize graphs

how brains and associative networks search for information

algorithm for finding the lowest common ancestors of a set of pairs of nodes in a tree, using the union-find data structure

algorithm for constructing maximum matchings on a graph

graph algorithm producing a vertex order consistent with BFS

concept in graph theory

algorithm in graph theory

minimum spanning forest algorithm that greedily deletes edges

heuristic pathfinding algorithm

algorithm for counting perfect matchings in planar graphs

graph search algorithm

a recursive backtracking algorithm for finding maximal cliques in an undirected graph

search algorithm

problem of maximizing the weight of the minimum-weight edge in the path between two vertices

Algorithm for minimising register usage