feat: Add the section of permutations problem. (#476)
* Add the section of permutations problem. * Update permutations_problem.mdpull/478/head
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/**
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* File: permutations_i.cpp
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* Created Time: 2023-04-24
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* Author: Krahets (krahets@163.com)
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*/
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#include "../include/include.hpp"
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/* 回溯算法:全排列 I */
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void backtrack(vector<int> &state, const vector<int> &choices, vector<bool> &selected, vector<vector<int>> &res) {
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// 当状态长度等于元素数量时,记录解
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if (state.size() == choices.size()) {
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res.push_back(state);
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return;
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}
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// 遍历所有选择
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for (int i = 0; i < choices.size(); i++) {
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int choice = choices[i];
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// 剪枝:不允许重复选择元素 且 不允许重复选择相等元素
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if (!selected[i]) {
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// 尝试
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selected[i] = true; // 做出选择
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state.push_back(choice); // 更新状态
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backtrack(state, choices, selected, res);
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// 回退
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selected[i] = false; // 撤销选择
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state.pop_back(); // 恢复到之前的状态
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}
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}
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}
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/* Driver Code */
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int main() {
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vector<int> nums = {1, 2, 3};
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// 回溯算法
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vector<int> state;
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vector<bool> selected(nums.size(), false);
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vector<vector<int>> res;
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backtrack(state, nums, selected, res);
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cout << "输入数组 nums = ";
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printVector(nums);
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cout << "所有排列 res = ";
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printVectorMatrix(res);
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return 0;
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}
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/**
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* File: permutations_ii.cpp
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* Created Time: 2023-04-24
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* Author: Krahets (krahets@163.com)
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*/
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#include "../include/include.hpp"
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/* 回溯算法:全排列 II */
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void backtrack(vector<int> &state, const vector<int> &choices, vector<bool> &selected, vector<vector<int>> &res) {
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// 当状态长度等于元素数量时,记录解
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if (state.size() == choices.size()) {
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res.push_back(state);
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return;
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}
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// 遍历所有选择
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unordered_set<int> duplicated;
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for (int i = 0; i < choices.size(); i++) {
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int choice = choices[i];
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// 剪枝:不允许重复选择元素 且 不允许重复选择相等元素
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if (!selected[i] && duplicated.find(choice) == duplicated.end()) {
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// 尝试
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duplicated.emplace(choice); // 记录选择过的元素值
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selected[i] = true; // 做出选择
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state.push_back(choice); // 更新状态
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backtrack(state, choices, selected, res);
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// 回退
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selected[i] = false; // 撤销选择
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state.pop_back(); // 恢复到之前的状态
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}
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}
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}
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/* Driver Code */
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int main() {
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vector<int> nums = {1, 1, 2};
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// 回溯算法
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vector<int> state;
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vector<bool> selected(nums.size(), false);
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vector<vector<int>> res;
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backtrack(state, nums, selected, res);
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cout << "输入数组 nums = ";
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printVector(nums);
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cout << "所有排列 res = ";
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printVectorMatrix(res);
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return 0;
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}
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/**
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* File: permutations_i.java
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* Created Time: 2023-04-24
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* Author: Krahets (krahets@163.com)
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*/
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package chapter_backtracking;
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import java.util.*;
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public class permutations_i {
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/* 回溯算法:全排列 I */
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public static void backtrack(List<Integer> state, int[] choices, boolean[] selected, List<List<Integer>> res) {
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// 当状态长度等于元素数量时,记录解
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if (state.size() == choices.length) {
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res.add(new ArrayList<Integer>(state));
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return;
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}
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// 遍历所有选择
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for (int i = 0; i < choices.length; i++) {
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int choice = choices[i];
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// 剪枝:不允许重复选择元素 且 不允许重复选择相等元素
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if (!selected[i]) {
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// 尝试
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selected[i] = true; // 做出选择
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state.add(choice); // 更新状态
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backtrack(state, choices, selected, res);
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// 回退
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selected[i] = false; // 撤销选择
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state.remove(state.size() - 1); // 恢复到之前的状态
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}
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}
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}
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public static void main(String[] args) {
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int[] nums = { 1, 2, 3 };
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List<List<Integer>> res = new ArrayList<List<Integer>>();
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// 回溯算法
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backtrack(new ArrayList<Integer>(), nums, new boolean[nums.length], res);
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System.out.println("输入数组 nums = " + Arrays.toString(nums));
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System.out.println("所有排列 res = " + res);
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}
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}
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/**
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* File: permutations_ii.java
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* Created Time: 2023-04-24
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* Author: Krahets (krahets@163.com)
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*/
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package chapter_backtracking;
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import java.util.*;
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public class permutations_ii {
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/* 回溯算法:全排列 II */
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public static void backtrack(List<Integer> state, int[] choices, boolean[] selected, List<List<Integer>> res) {
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// 当状态长度等于元素数量时,记录解
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if (state.size() == choices.length) {
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res.add(new ArrayList<Integer>(state));
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return;
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}
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// 遍历所有选择
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Set<Integer> duplicated = new HashSet<Integer>();
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for (int i = 0; i < choices.length; i++) {
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int choice = choices[i];
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// 剪枝:不允许重复选择元素 且 不允许重复选择相等元素
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if (!selected[i] && !duplicated.contains(choice)) {
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// 尝试
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duplicated.add(choice); // 记录选择过的元素值
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selected[i] = true; // 做出选择
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state.add(choice); // 更新状态
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backtrack(state, choices, selected, res);
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// 回退
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selected[i] = false; // 撤销选择
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state.remove(state.size() - 1); // 恢复到之前的状态
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}
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}
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}
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public static void main(String[] args) {
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int[] nums = { 1, 2, 2 };
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List<List<Integer>> res = new ArrayList<List<Integer>>();
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// 回溯算法
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backtrack(new ArrayList<Integer>(), nums, new boolean[nums.length], res);
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System.out.println("输入数组 nums = " + Arrays.toString(nums));
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System.out.println("所有排列 res = " + res);
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}
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}
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"""
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File: permutations_i.py
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Created Time: 2023-04-15
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Author: Krahets (krahets@163.com)
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"""
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import sys, os.path as osp
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sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
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from modules import *
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def backtrack(
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state: list[int], choices: list[int], selected: list[bool], res: list[list[int]]
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):
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"""回溯算法:全排列 I"""
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# 当状态长度等于元素数量时,记录解
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if len(state) == len(choices):
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res.append(list(state))
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return
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# 遍历所有选择
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for i, choice in enumerate(choices):
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# 剪枝:不允许重复选择元素
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if not selected[i]:
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# 尝试
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selected[i] = True # 做出选择
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state.append(choice) # 更新状态
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backtrack(state, choices, selected, res)
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# 回退
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selected[i] = False # 撤销选择
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state.pop() # 恢复到之前的状态
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"""Driver Code"""
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if __name__ == "__main__":
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nums = [1, 2, 3]
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res = []
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# 回溯算法
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backtrack(state=[], choices=nums, selected=[False] * len(nums), res=res)
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print(f"输入数组 nums = {nums}")
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print(f"所有排列 res = {res}")
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"""
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File: permutations_ii.py
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Created Time: 2023-04-15
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Author: Krahets (krahets@163.com)
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"""
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import sys, os.path as osp
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sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
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from modules import *
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def backtrack(
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state: list[int], choices: list[int], selected: list[bool], res: list[list[int]]
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):
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"""回溯算法:全排列 II"""
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# 当状态长度等于元素数量时,记录解
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if len(state) == len(choices):
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res.append(list(state))
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return
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# 遍历所有选择
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duplicated = set[int]()
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for i, choice in enumerate(choices):
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# 剪枝:不允许重复选择元素 且 不允许重复选择相等元素
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if not selected[i] and choice not in duplicated:
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# 尝试
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duplicated.add(choice) # 记录选择过的元素值
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selected[i] = True # 做出选择
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state.append(choice) # 更新状态
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backtrack(state, choices, selected, res)
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# 回退
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selected[i] = False # 撤销选择
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state.pop() # 恢复到之前的状态
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"""Driver Code"""
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if __name__ == "__main__":
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nums = [1, 2, 2]
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res = []
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# 回溯算法
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backtrack(state=[], choices=nums, selected=[False] * len(nums), res=res)
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print(f"输入数组 nums = {nums}")
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print(f"所有排列 res = {res}")
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After Width: | Height: | Size: 55 KiB |
After Width: | Height: | Size: 88 KiB |
After Width: | Height: | Size: 61 KiB |
After Width: | Height: | Size: 79 KiB |
After Width: | Height: | Size: 73 KiB |
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# 全排列问题
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全排列问题是回溯算法的一个典型应用。它的定义是在给定一个集合(如一个数组或字符串)的情况下,找出这个集合中元素的所有可能的排列。
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如下表所示,展示了输入数组和对应的所有排列。
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<div class="center-table" markdown>
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| 输入数组 | 所有排列 |
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| :-------- | :--------------------------------------------------------------- |
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| [1] | [1] |
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| [1, 2] | [1, 2], [2, 1] |
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| [1, 2, 3] | [1, 2, 3], [1, 3, 2], [2, 1, 3], [2, 3, 1], [3, 1, 2], [3, 2, 1] |
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</div>
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## 无重复的情况
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!!! question "输入一个整数数组,数组中不包含重复元素,返回所有可能的排列。"
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**从回溯算法的角度看,我们可以把生成排列的过程想象成一系列选择的结果**。假设输入数组为 `[1, 2, 3]` ,如果我们先选择 `1` 、再选择 `3` 、最后选择 `2` ,则获得排列 `[1, 3, 2]` 。回退表示撤销一个选择,之后继续尝试其他选择。
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从回溯算法代码的角度看,候选集合 `choices` 是输入数组中的所有元素,状态 `state` 是直至目前已被选择的元素。注意,每个元素只允许被选择一次,**因此在遍历选择时,应当排除已经选择过的元素**。
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如下图所示,我们可以将搜索过程展开成一个递归树,树中的每个节点代表当前状态 `state` 。从根节点开始,经过三轮选择后到达叶节点,每个叶节点都对应一个排列。
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![全排列的递归树](permutations_problem.assets/permutations_i.png)
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想清楚以上信息之后,我们就可以在框架代码中做“完形填空”了。为了缩短代码行数,我们不单独实现框架代码中的各个函数,而是将他们展开在 `backtrack()` 函数中。
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=== "Java"
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```java title="permutations_i.java"
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[class]{permutations_i}-[func]{backtrack}
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```
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=== "C++"
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```cpp title="permutations_i.cpp"
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[class]{}-[func]{backtrack}
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```
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=== "Python"
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```python title="permutations_i.py"
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[class]{}-[func]{backtrack}
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```
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=== "Go"
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```go title="permutations_i.go"
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[class]{}-[func]{backtrack}
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```
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=== "JavaScript"
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```javascript title="permutations_i.js"
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[class]{}-[func]{backtrack}
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```
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=== "TypeScript"
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```typescript title="permutations_i.ts"
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[class]{}-[func]{backtrack}
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```
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=== "C"
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```c title="permutations_i.c"
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[class]{}-[func]{backtrack}
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```
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=== "C#"
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```csharp title="permutations_i.cs"
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[class]{permutations_i}-[func]{backtrack}
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```
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=== "Swift"
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```swift title="permutations_i.swift"
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[class]{}-[func]{backtrack}
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```
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=== "Zig"
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```zig title="permutations_i.zig"
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[class]{}-[func]{backtrack}
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```
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需要重点关注的是,我们引入了一个布尔型数组 `selected` ,它的长度与输入数组长度相等,其中 `selected[i]` 表示 `choices[i]` 是否已被选择。我们利用 `selected` 避免某个元素被重复选择,从而实现剪枝。
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如下图所示,假设我们第一轮选择 1 ,第二轮选择 3 ,第三轮选择 2 ,则需要在第二轮剪掉元素 1 的分支,在第三轮剪掉元素 1, 3 的分支。**从本质上理解,此剪枝操作可将搜索空间大小从 $O(n^n)$ 降低至 $O(n!)$** 。
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![全排列剪枝示例](permutations_problem.assets/permutations_i_pruning.png)
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## 考虑重复的情况
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!!! question "输入一个整数数组,**数组中可能包含重复元素**,返回所有不重复的排列。"
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假设输入数组为 `[1, 1, 2]` 。为了方便区分两个重复的元素 `1` ,接下来我们将第二个元素记为 `1'` 。如下图所示,上述方法生成的排列有一半都是重复的。
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![重复排列](permutations_problem.assets/permutations_ii.png)
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那么,如何去除重复的排列呢?最直接地,我们可以借助一个哈希表,直接对排列结果进行去重。然而,这样做不够优雅,因为生成重复排列的搜索分支是没有必要的,应当被提前识别并剪枝,这样可以提升算法效率。
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观察发现,在第一轮中,选择 `1` 或选择 `1'` 是等价的,因为在这两个选择之下生成的所有排列都是重复的。因此,我们应该把 `1'` 剪枝掉。同理,在第一轮选择 `2` 后,第二轮选择中的 `1` 和 `1'` 也会产生重复分支,因此也需要将第二轮的 `1'` 剪枝。
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![重复排列剪枝](permutations_problem.assets/permutations_ii_pruning.png)
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本质上看,**我们的目标是实现在某一轮选择中,多个相等的元素仅被选择一次**。因此,在上一题的代码的基础上,我们考虑在每一轮选择中开启一个哈希表 `duplicated` ,用于记录该轮中已经尝试过的元素,并将重复元素剪枝。
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=== "Java"
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```java title="permutations_ii.java"
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[class]{permutations_ii}-[func]{backtrack}
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```
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=== "C++"
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```cpp title="permutations_ii.cpp"
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[class]{}-[func]{backtrack}
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```
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=== "Python"
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|
||||
```python title="permutations_ii.py"
|
||||
[class]{}-[func]{backtrack}
|
||||
```
|
||||
|
||||
=== "Go"
|
||||
|
||||
```go title="permutations_ii.go"
|
||||
[class]{}-[func]{backtrack}
|
||||
```
|
||||
|
||||
=== "JavaScript"
|
||||
|
||||
```javascript title="permutations_ii.js"
|
||||
[class]{}-[func]{backtrack}
|
||||
```
|
||||
|
||||
=== "TypeScript"
|
||||
|
||||
```typescript title="permutations_ii.ts"
|
||||
[class]{}-[func]{backtrack}
|
||||
```
|
||||
|
||||
=== "C"
|
||||
|
||||
```c title="permutations_ii.c"
|
||||
[class]{}-[func]{backtrack}
|
||||
```
|
||||
|
||||
=== "C#"
|
||||
|
||||
```csharp title="permutations_ii.cs"
|
||||
[class]{permutations_ii}-[func]{backtrack}
|
||||
```
|
||||
|
||||
=== "Swift"
|
||||
|
||||
```swift title="permutations_ii.swift"
|
||||
[class]{}-[func]{backtrack}
|
||||
```
|
||||
|
||||
=== "Zig"
|
||||
|
||||
```zig title="permutations_ii.zig"
|
||||
[class]{}-[func]{backtrack}
|
||||
```
|
||||
|
||||
注意,虽然 `selected` 和 `duplicated` 都起到剪枝的作用,但他们剪掉的是不同的分支:
|
||||
|
||||
- **剪枝条件一**:整个搜索过程中只有一个 `selected` 。它记录的是当前状态中包含哪些元素,作用是避免某个元素在 `state` 中重复出现。
|
||||
- **剪枝条件二**:每轮选择(即每个开启的 `backtrack` 函数)都包含一个 `duplicated` 。它记录的是在遍历中哪些元素已被选择过,作用是保证相等元素只被选择一次,以避免产生重复的搜索分支。
|
||||
|
||||
下图展示了两个剪枝条件的生效范围。注意,树中的每个节点代表一个选择,从根节点到叶节点的路径上的各个节点构成一个排列。
|
||||
|
||||
![两种剪枝条件的作用范围](permutations_problem.assets/permutations_ii_pruning_summary.png)
|
Loading…
Reference in new issue