利用与线性方程组迭代求解方法相关的遍历查找图形的连接部分

A. V. Prolubnikov
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引用次数: 0

摘要

要解决图上的许多问题,都要用到图遍历,其通常的变体是深度优先搜索和广度优先搜索。在构建查找图中连通成分的高效算法时,通常会选择广度优先搜索。利用修改过的图邻接矩阵和适当指定的右边来求解线性方程组的简单迭代方法,可以视为图遍历算法。一般来说,这种遍历算法既不等同于深度优先搜索,也不等同于广度优先搜索。这种遍历算法的例子是与高斯-赛德尔法相关的算法。对于一个任意的连通图,要访问其所有顶点,该算法所需的迭代次数并不比 BFS 多。对于问题的大量实例,所需的迭代次数会更少。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Finding connected components of a graph using traversals associated with iterative methods for solving systems of linear equations
To solve many problems on graphs, graph traversals are used, the usual variants of which are the depth-first search and the breadth-first search. Implementing a graph traversal we consequently reach all vertices of the graph that belong to a connected component. The breadth-first search is the usual choice when constructing efficient algorithms for finding connected components of a graph. Methods of simple iteration for solving systems of linear equations with modified graph adjacency matrices and with the properly specified right-hand side can be considered as graph traversal algorithms. These traversal algorithms, generally speaking, turn out to be non-equivalent neither to the depth-first search nor the breadth-first search. The example of such a traversal algorithm is the one associated with the Gauss-Seidel method. For an arbitrary connected graph, to visit all its vertices, the algorithm requires not more iterations than that is required for BFS. For a large number of instances of the problem, fewer iterations will be required.
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