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

Java中的DFS迭代:

//DFS: Iterative
private Boolean DFSIterative(Node root, int target) {
    if (root == null)
        return false;
    Stack<Node> _stack = new Stack<Node>();
    _stack.push(root);
    while (_stack.size() > 0) {
        Node temp = _stack.peek();
        if (temp.data == target)
            return true;
        if (temp.left != null)
            _stack.push(temp.left);
        else if (temp.right != null)
            _stack.push(temp.right);
        else
            _stack.pop();
    }
    return false;
}

其他回答

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)

}

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

你可以使用堆栈。我用邻接矩阵实现了图:

void DFS(int current){
    for(int i=1; i<N; i++) visit_table[i]=false;
    myStack.push(current);
    cout << current << "  ";
    while(!myStack.empty()){
        current = myStack.top();
        for(int i=0; i<N; i++){
            if(AdjMatrix[current][i] == 1){
                if(visit_table[i] == false){ 
                    myStack.push(i);
                    visit_table[i] = true;
                    cout << i << "  ";
                }
                break;
            }
            else if(!myStack.empty())
                myStack.pop();
        }
    }
}

DFS:

list nodes_to_visit = {root};
while( nodes_to_visit isn't empty ) {
  currentnode = nodes_to_visit.take_first();
  nodes_to_visit.prepend( currentnode.children );
  //do something
}

BFS:

list nodes_to_visit = {root};
while( nodes_to_visit isn't empty ) {
  currentnode = nodes_to_visit.take_first();
  nodes_to_visit.append( currentnode.children );
  //do something
}

两者的对称相当酷。

更新:如前所述,take_first()删除并返回列表中的第一个元素。

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