graph-search algorithm
111Tree traversal — Graph and tree search algorithms Alpha beta pruning A* B* Beam Bellman–Ford algorithm Best first Bidirectional …
112Strongly connected component — Graph with strongly connected components marked A directed graph is called strongly connected if there is a path from each vertex in the graph to every other vertex. In particular, this means paths in each direction; a path from a to b and also a …
1132-satisfiability — In computer science, 2 satisfiability (abbreviated as 2 SAT or just 2SAT) is the problem of determining whether a collection of two valued (Boolean or binary) variables with constraints on pairs of variables can be assigned values satisfying all… …
114Travelling salesman problem — The travelling salesman problem (TSP) is an NP hard problem in combinatorial optimization studied in operations research and theoretical computer science. Given a list of cities and their pairwise distances, the task is to find a shortest… …
115Maximum flow problem — An example of a flow network with a maximum flow. The source is s, and the sink t. The numbers denote flow and capacity. In optimization theory, the maximum flow problem is to find a feasible flow through a single source, single sink flow network …
116List of mathematics articles (G) — NOTOC G G₂ G delta space G networks Gδ set G structure G test G127 G2 manifold G2 structure Gabor atom Gabor filter Gabor transform Gabor Wigner transform Gabow s algorithm Gabriel graph Gabriel s Horn Gain graph Gain group Galerkin method… …
117Simulated annealing — (SA) is a generic probabilistic meta algorithm for the global optimization problem, namely locating a good approximation to the global optimum of a given function in a large search space. It is often used when the search space is discrete (e.g.,… …
118Dynamic programming — For the programming paradigm, see Dynamic programming language. In mathematics and computer science, dynamic programming is a method for solving complex problems by breaking them down into simpler subproblems. It is applicable to problems… …
119Cycle detection — This article is about iterated functions. For another use, see Cycle detection (graph theory). In computer science, cycle detection is the algorithmic problem of finding a cycle in a sequence of iterated function values. For any function ƒ that… …
120Constraint learning — In constraint satisfaction backtracking algorithms, constraint learning is a technique for improving efficiency. It works by recording new constraints whenever an inconsistency is found. This new constraint may reduce the search space, as future… …
