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Dijkstra's algorithm finds the shortest path from a given source node to every other node.: 196–206 It can also be used to find the shortest path to a specific destination node, by terminating the algorithm once the shortest path to the destination node is known. For example, if the nodes of the graph represent cities, and the costs of edges ...
Shortest path (A, C, E, D, F) 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. The problem of finding the shortest path between two intersections ...
The numbers beside the vertices indicate the distance from the root vertex. In mathematics and computer science, a shortest-path tree rooted at a vertex v of a connected, undirected graph G is a spanning tree T of G, such that the path distance from root v to any other vertex u in T is the shortest path distance from v to u in G .
Directed acyclic graph. In mathematics, particularly graph theory, and computer science, a directed acyclic graph ( DAG) is a directed graph with no directed cycles. That is, it consists of vertices and edges (also called arcs ), with each edge directed from one vertex to another, such that following those directions will never form a closed ...
Google APIs are application programming interfaces ( APIs) developed by Google which allow communication with Google Services and their integration to other services. Examples of these include Search, Gmail, Translate or Google Maps. Third-party apps can use these APIs to take advantage of or extend the functionality of the existing services.
A* search algorithm. A* (pronounced "A-star") is a graph traversal and pathfinding algorithm, which is used in many fields of computer science due to its completeness, optimality, and optimal efficiency. [1] Given a weighted graph, a source node and a goal node, the algorithm finds the shortest path (with respect to the given weights) from ...
Optimal. yes (for unweighted graphs) In computer science, iterative deepening search or more specifically iterative deepening depth-first search [2] (IDS or IDDFS) is a state space /graph search strategy in which a depth-limited version of depth-first search is run repeatedly with increasing depth limits until the goal is found.
Contraction hierarchies is a speed-up method optimized to exploit properties of graphs representing road networks. [2] The speed-up is achieved by creating shortcuts in a preprocessing phase which are then used during a shortest-path query to skip over "unimportant" vertices. [2] This is based on the observation that road networks are highly ...