我正在寻找一个非二叉树的非递归深度优先搜索算法。任何帮助都非常感激。


当前回答

完整的示例工作代码,没有堆栈:

import java.util.*;

class Graph {
private List<List<Integer>> adj;

Graph(int numOfVertices) {
    this.adj = new ArrayList<>();
    for (int i = 0; i < numOfVertices; ++i)
        adj.add(i, new ArrayList<>());
}

void addEdge(int v, int w) {
    adj.get(v).add(w); // Add w to v's list.
}

void DFS(int v) {
    int nodesToVisitIndex = 0;
    List<Integer> nodesToVisit = new ArrayList<>();
    nodesToVisit.add(v);
    while (nodesToVisitIndex < nodesToVisit.size()) {
        Integer nextChild= nodesToVisit.get(nodesToVisitIndex++);// get the node and mark it as visited node by inc the index over the element.
        for (Integer s : adj.get(nextChild)) {
            if (!nodesToVisit.contains(s)) {
                nodesToVisit.add(nodesToVisitIndex, s);// add the node to the HEAD of the unvisited nodes list.
            }
        }
        System.out.println(nextChild);
    }
}

void BFS(int v) {
    int nodesToVisitIndex = 0;
    List<Integer> nodesToVisit = new ArrayList<>();
    nodesToVisit.add(v);
    while (nodesToVisitIndex < nodesToVisit.size()) {
        Integer nextChild= nodesToVisit.get(nodesToVisitIndex++);// get the node and mark it as visited node by inc the index over the element.
        for (Integer s : adj.get(nextChild)) {
            if (!nodesToVisit.contains(s)) {
                nodesToVisit.add(s);// add the node to the END of the unvisited node list.
            }
        }
        System.out.println(nextChild);
    }
}

public static void main(String args[]) {
    Graph g = new Graph(5);

    g.addEdge(0, 1);
    g.addEdge(0, 2);
    g.addEdge(1, 2);
    g.addEdge(2, 0);
    g.addEdge(2, 3);
    g.addEdge(3, 3);
    g.addEdge(3, 1);
    g.addEdge(3, 4);

    System.out.println("Breadth First Traversal- starting from vertex 2:");
    g.BFS(2);
    System.out.println("Depth First Traversal- starting from vertex 2:");
    g.DFS(2);
}}

输出: 宽度优先遍历-从顶点2开始: 2 0 3. 1 4 深度优先遍历-从顶点2开始: 2 3. 4 1 0

其他回答

伪代码基于@biziclop的答案:

只使用基本结构:变量、数组、if、while和for 函数getNode(id)和getChildren(id) 假设已知节点数N


注意:我从1开始使用数组索引,而不是0。

广度优先

S = Array(N)
S[1] = 1; // root id
cur = 1;
last = 1
while cur <= last
    id = S[cur]
    node = getNode(id)
    children = getChildren(id)

    n = length(children)
    for i = 1..n
        S[ last+i ] = children[i]
    end
    last = last+n
    cur = cur+1

    visit(node)
end

深度优先

S = Array(N)
S[1] = 1; // root id
cur = 1;
while cur > 0
    id = S[cur]
    node = getNode(id)
    children = getChildren(id)

    n = length(children)
    for i = 1..n
        // assuming children are given left-to-right
        S[ cur+i-1 ] = children[ n-i+1 ] 

        // otherwise
        // S[ cur+i-1 ] = children[i] 
    end
    cur = cur+n-1

    visit(node)
end

使用ES6生成器的非递归DFS

class Node {
  constructor(name, childNodes) {
    this.name = name;
    this.childNodes = childNodes;
    this.visited = false;
  }
}

function *dfs(s) {
  let stack = [];
  stack.push(s);
  stackLoop: while (stack.length) {
    let u = stack[stack.length - 1]; // peek
    if (!u.visited) {
      u.visited = true; // grey - visited
      yield u;
    }

    for (let v of u.childNodes) {
      if (!v.visited) {
        stack.push(v);
        continue stackLoop;
      }
    }

    stack.pop(); // black - all reachable descendants were processed 
  }    
}

它与典型的非递归DFS不同,可以很容易地检测给定节点的所有可达后代何时被处理,并维护列表/堆栈中的当前路径。

基于biziclops的ES6实现很棒的答案:

root = { text: "root", children: [{ text: "c1", children: [{ text: "c11" }, { text: "c12" }] }, { text: "c2", children: [{ text: "c21" }, { text: "c22" }] }, ] } console.log("DFS:") DFS(root, node => node.children, node => console.log(node.text)); console.log("BFS:") BFS(root, node => node.children, node => console.log(node.text)); function BFS(root, getChildren, visit) { let nodesToVisit = [root]; while (nodesToVisit.length > 0) { const currentNode = nodesToVisit.shift(); nodesToVisit = [ ...nodesToVisit, ...(getChildren(currentNode) || []), ]; visit(currentNode); } } function DFS(root, getChildren, visit) { let nodesToVisit = [root]; while (nodesToVisit.length > 0) { const currentNode = nodesToVisit.shift(); nodesToVisit = [ ...(getChildren(currentNode) || []), ...nodesToVisit, ]; visit(currentNode); } }

使用堆栈来跟踪节点

Stack<Node> s;

s.prepend(tree.head);

while(!s.empty) {
    Node n = s.poll_front // gets first node

    // do something with q?

    for each child of n: s.prepend(child)

}
Stack<Node> stack = new Stack<>();
stack.add(root);
while (!stack.isEmpty()) {
    Node node = stack.pop();
    System.out.print(node.getData() + " ");

    Node right = node.getRight();
    if (right != null) {
        stack.push(right);
    }

    Node left = node.getLeft();
    if (left != null) {
        stack.push(left);
    }
}