传递闭包算法解析:深度优先搜索 vs 广度优先搜索
引言:
传递闭包算法是图论中一个重要的算法,用于构建关系图的传递闭包。而在实现传递闭包算法时,常见的两种搜索策略是深度优先搜索(DFS)和广度优先搜索(BFS)。本文将详细介绍这两种搜索策略,并通过具体的代码示例来解析它们在传递闭包算法中的应用。
一、深度优先搜索(DFS):
深度优先搜索是一种先探索深度节点,再回溯到更浅层节点的搜索策略。在传递闭包算法中,我们可以利用DFS来构建关系图的传递闭包。下面我们通过以下示例代码来说明DFS在传递闭包算法中的应用:
# 传递闭包算法-深度优先搜索 def dfs(graph, start, visited): visited[start] = True for neighbor in graph[start]: if not visited[neighbor]: dfs(graph, neighbor, visited) def transitive_closure_dfs(graph): num_nodes = len(graph) closure_table = [[0] * num_nodes for _ in range(num_nodes)] for node in range(num_nodes): visited = [False] * num_nodes dfs(graph, node, visited) for i in range(num_nodes): if visited[i]: closure_table[node][i] = 1 return closure_table