Search results
Results from the WOW.Com Content Network
UML class diagram of a Graph (abstract data type) The basic operations provided by a graph data structure G usually include: [1] adjacent(G, x, y): tests whether there is an edge from the vertex x to the vertex y; neighbors(G, x): lists all vertices y such that there is an edge from the vertex x to the vertex y;
For example, if both r and source connect to target and they lie on different shortest paths through target (because the edge cost is the same in both cases), then both r and source are added to prev[target]. When the algorithm completes, prev[] data structure describes a graph that is a subset of the original graph with some edges removed. Its ...
A data structure known as a hash table.. In computer science, a data structure is a data organization and storage format that is usually chosen for efficient access to data. [1] [2] [3] More precisely, a data structure is a collection of data values, the relationships among them, and the functions or operations that can be applied to the data, [4] i.e., it is an algebraic structure about data.
The problem of graph exploration can be seen as a variant of graph traversal. It is an online problem, meaning that the information about the graph is only revealed during the runtime of the algorithm. A common model is as follows: given a connected graph G = (V, E) with non-negative edge weights. The algorithm starts at some vertex, and knows ...
Many graph-based data structures are used in computer science and related fields: Graph; Adjacency list; Adjacency matrix; Graph-structured stack; Scene graph; Decision tree. Binary decision diagram; Zero-suppressed decision diagram; And-inverter graph; Directed graph; Directed acyclic graph; Propositional directed acyclic graph; Multigraph ...
A graph with three vertices and three edges. A graph (sometimes called an undirected graph to distinguish it from a directed graph, or a simple graph to distinguish it from a multigraph) [4] [5] is a pair G = (V, E), where V is a set whose elements are called vertices (singular: vertex), and E is a set of unordered pairs {,} of vertices, whose elements are called edges (sometimes links or lines).
For a graph with E edges and V vertices, Kruskal's algorithm can be shown to run in time O(E log E) time, with simple data structures. This time bound is often written instead as O ( E log V ) , which is equivalent for graphs with no isolated vertices, because for these graphs V /2 ≤ E < V 2 and the logarithms of V and E are again within a ...
Prim's algorithm has many applications, such as in the generation of this maze, which applies Prim's algorithm to a randomly weighted grid graph. The time complexity of Prim's algorithm depends on the data structures used for the graph and for ordering the edges by weight, which can be done using a priority queue. The following table shows the ...