Editing List of algorithms (section)

===Graph algorithms===
{{further|Graph theory|:Category:Graph algorithms}}
* [[Coloring algorithm]]: Graph coloring algorithm.
* [[Hopcroft–Karp algorithm]]: convert a bipartite graph to a [[maximum cardinality matching]]
* [[Hungarian algorithm]]: algorithm for finding a [[perfect matching]]
* [[Prüfer sequence|Prüfer coding]]: conversion between a labeled tree and its [[Prüfer sequence]]
* [[Tarjan's off-line lowest common ancestors algorithm]]: computes [[lowest common ancestor]]s for pairs of nodes in a tree
* [[Topological sorting|Topological sort]]: finds linear order of nodes (e.g. jobs) based on their dependencies.

====Graph drawing====
{{further|Graph drawing}}
* [[Force-based algorithms (graph drawing)|Force-based algorithms]] (also known as force-directed algorithms or spring-based algorithm)
* [[Spectral layout]]

====Network theory====
{{further|Network theory}}
* Network analysis
** Link analysis
*** [[Girvan–Newman algorithm]]: detect communities in complex systems
*** Web link analysis
**** [[Hyperlink-Induced Topic Search]] (HITS) (also known as [[Hubs and authorities]])
**** [[PageRank]]
**** [[TrustRank]]
* [[Flow network]]s
** [[Dinic's algorithm]]: is a [[strongly polynomial]] algorithm for computing the [[maximum flow]] in a [[flow network]].
** [[Edmonds–Karp algorithm]]: implementation of Ford–Fulkerson
** [[Ford–Fulkerson algorithm]]: computes the [[maximum flow problem|maximum flow]] in a graph
** [[Karger's algorithm]]: a Monte Carlo method to compute the [[minimum cut]] of a connected graph
** [[Push–relabel algorithm]]: computes a [[maximum flow problem|maximum flow]] in a graph

====Routing for graphs====
* [[Edmonds' algorithm]] (also known as Chu–Liu/Edmonds' algorithm): find maximum or minimum branchings
* [[Euclidean minimum spanning tree]]: algorithms for computing the minimum spanning tree of a set of points in the plane
* [[Longest path problem]]: find a simple path of maximum length in a given graph
* [[Minimum spanning tree]]
** [[Borůvka's algorithm]]
** [[Kruskal's algorithm]]
** [[Prim's algorithm]]
** [[Reverse-delete algorithm]]
* [[Nonblocking minimal spanning switch]] say, for a [[telephone exchange]]
* [[Vehicle routing problem]]
** Clarke and Wright Saving algorithm
* [[Shortest path problem]]
** [[Bellman–Ford algorithm]]: computes [[shortest path problem|shortest paths]] in a weighted graph (where some of the edge weights may be negative)
** [[Dijkstra's algorithm]]: computes [[shortest path problem|shortest paths]] in a graph with non-negative edge weights
** [[Floyd–Warshall algorithm]]: solves the [[shortest path problem#All-pairs shortest paths|all pairs shortest path]] problem in a weighted, directed graph
** [[Johnson's algorithm]]: all pairs shortest path algorithm in sparse weighted directed graph
<!-- ** [[Perturbation methods]]: an algorithm that computes a locally [[shortest path problem|shortest paths]] in a graph -->
* [[Transitive closure]] problem: find the [[transitive closure]] of a given binary relation
* [[Traveling salesman problem]]
** [[Christofides algorithm]]
** [[Nearest neighbour algorithm]]
* [[Warnsdorff's rule]]: a heuristic method for solving the [[Knight's tour]] problem

====Graph search====
{{further|State space search|Graph search algorithm}}
* [[A* search algorithm|A*]]: special case of best-first search that uses heuristics to improve speed
* [[B*]]: a best-first graph search algorithm that finds the least-cost path from a given initial node to any goal node (out of one or more possible goals)
* [[Backtracking]]: abandons partial solutions when they are found not to satisfy a complete solution
* [[Beam search]]: is a heuristic search algorithm that is an optimization of [[best-first search]] that reduces its memory requirement
* [[Beam stack search]]: integrates backtracking with [[beam search]]
* [[Best-first search]]: traverses a graph in the order of likely importance using a [[priority queue]]
* [[Bidirectional search]]: find the shortest path from an initial vertex to a goal vertex in a directed graph
* [[Breadth-first search]]: traverses a graph level by level
* [[Brute-force search]]: an exhaustive and reliable search method, but computationally inefficient in many applications
* [[D*]]: an [[incremental heuristic search]] algorithm
* [[Depth-first search]]: traverses a graph branch by branch
* [[Dijkstra's algorithm]]: a special case of A* for which no heuristic function is used
* [[General Problem Solver]]: a seminal theorem-proving algorithm intended to work as a universal problem solver machine.
* [[Iterative deepening depth-first search]] (IDDFS): a state space search strategy
* [[Jump point search]]: an optimization to A* which may reduce computation time by an order of magnitude using further heuristics
* [[Lexicographic breadth-first search]] (also known as Lex-BFS): a linear time algorithm for ordering the vertices of a graph
* [[Uniform-cost search]]: a [[Tree traversal|tree search]] that finds the lowest-cost route where costs vary
* [[SSS*]]: state space search traversing a game tree in a best-first fashion similar to that of the A* search algorithm

====Subgraphs====
* [[Clique (graph theory)|Cliques]]
** [[Bron–Kerbosch algorithm]]: a technique for finding [[maximal clique]]s in an undirected graph
** [[MaxCliqueDyn maximum clique algorithm]]: find a [[maximum clique]] in an undirected graph
* [[Strongly connected components]]
** [[Path-based strong component algorithm]]
** [[Kosaraju's algorithm]]
** [[Tarjan's strongly connected components algorithm]]
* [[Subgraph isomorphism problem]]