leetcode|37. Sudoku Solver

本文介绍了一种使用回溯法解决数独问题的算法。通过递归地尝试填充空格并验证每一步的合法性,最终找到唯一解。文章详细解释了如何利用三个辅助矩阵来跟踪行、列和区块的状态,以确保数独的正确性和唯一性。

Sudoku Solver

Write a program to solve a Sudoku puzzle by filling the empty cells.

Empty cells are indicated by the character ‘.’.

You may assume that there will be only one unique solution.

const static int ans=9;
   bool rows[ans][ans];
   bool cols[ans][ans];
   bool area[ans][ans];
   
   void initArray(vector<vector<char>>& board){
     memset(rows,false,sizeof(rows));
     memset(cols,false,sizeof(cols));
     memset(area,false,sizeof(area));
     isValidSudoku(board,0,0,0,false);
   }
   
   void solveSudoku(vector<vector<char>>& board){
       initArray(board);
       if(solveSudoku1(board)) return;
   }
    bool solveSudoku1(vector<vector<char>>& board) {
        for(int i=0;i<board.size();i++){
            for(int j=0;j<board[i].size();j++){
                if(board[i][j]=='.'){
                    for(int k=0;k<9;k++){
                        if(!isValidSudoku(board,i,j,k,true))
                              continue;
                        board[i][j]=k+'1';
                        rows[i][k]=cols[k][j]=area[k/3+(i/3)*3][k%3+(j/3)*3]=true;
                        if(solveSudoku1(board)){
                            return true;
                        }
                        board[i][j]='.';
                        rows[i][k]=cols[k][j]=area[k/3+(i/3)*3][k%3+(j/3)*3]=false;
                    }
                    return false;
                }
            }
        }
        return true;
    }<pre name="code" class="cpp">bool isValidSudoku(vector<vector<char>>& board,int r,int c,int k,bool mode) {//一直没有传进去k值
        if(board.size()!=9) return false;
        for(int i=0;i<0;i++){
            if(board[i].size()!=9) return false;
        }
        if(mode){
            int pos=k;
            //check area
            int ref_row=r/3;//对应0,1,2
            int ref_col=c/3;//对应0,1,2
            //对应9个area区域
            int area_i=pos/3+ref_row*3;
            int area_j=pos%3+ref_col*3;
            if(rows[r][pos]||cols[pos][c]||area[area_i][area_j])
                    return false;
            return true;
        }
        //下面用来初始化最初的棋盘
        for(int i=0;i<board.size();i++){
            for(int j=0;j<board[i].size();j++){
                if(board[i][j]=='.') continue;
                int pos=board[i][j]-'1';
                //check area
                int ref_row=i/3;//对应0,1,2
                int ref_col=j/3;//对应0,1,2
                //对应9个area区域
                int area_i=pos/3+ref_row*3;
                int area_j=pos%3+ref_col*3;
                rows[i][pos]=cols[pos][j]=area[area_i][area_j]=true;
            }
        }
    }

上种解法是借助了三个矩阵辅助记录。可以减小空间。

把空间复杂度降低为O(1)

bool solveSudoku(vector<vector<char> > &board) {
for (int i = 0; i < 9; ++i)
for (int j = 0; j < 9; ++j) {
if (board[i][j] == '.') {
for (int k = 0; k < 9; ++k) {
board[i][j] = '1' + k;
if (isValid(board, i, j) && solveSudoku(board))
return true;
board[i][j] = '.';
}
return false;
}
}
return true;
}

    // 检查 (x, y) 是否合法
bool isValid(const vector<vector<char> > &board, int x, int y) {
int i, j;
for (i = 0; i < 9; i++) // 检查 y 列
if (i != x && board[i][y] == board[x][y])
return false;
for (j = 0; j < 9; j++) // 检查 x 行
if (j != y && board[x][j] == board[x][y])
return false;
for (i = 3 * (x / 3); i < 3 * (x / 3 + 1); i++)
for (j = 3 * (y / 3); j < 3 * (y / 3 + 1); j++)
if ((i != x || j != y) && board[i][j] == board[x][y])
return false;
return true;
}
### LeetCode Problem 37: Sudoku Solver #### Problem Description The task involves solving a partially filled Sudoku puzzle. The input is represented as a two-dimensional integer array `board` where each element can be either a digit from '1' to '9' or '.' indicating empty cells. #### Solution Approach To solve this problem, one approach uses backtracking combined with depth-first search (DFS). This method tries placing numbers between 1 and 9 into every cell that contains '.', checking whether it leads to a valid solution by ensuring no conflicts arise within rows, columns, and subgrids[^6]. ```cpp void solveSudoku(vector<vector<char>>& board) { backtrack(board); } bool backtrack(vector<vector<char>> &board){ for(int row = 0; row < 9; ++row){ for(int col = 0; col < 9; ++col){ if(board[row][col] != '.') continue; for(char num='1';num<='9';++num){ if(isValidPlacement(board,row,col,num)){ placeNumber(num,board,row,col); if(backtrack(board)) return true; removeNumber(num,board,row,col); } } return false; } } return true; } ``` In the provided code snippet: - A function named `solveSudoku()` initiates the process. - Within `backtrack()`, nested loops iterate over all positions in the grid looking for unassigned spots denoted by '.' - For any such spot found, attempts are made to insert digits ranging from '1' through '9'. - Before insertion, validation checks (`isValidPlacement`) ensure compliance with Sudoku rules regarding uniqueness per row/column/subgrid constraints. - If inserting a number results in reaching a dead end without finding a complete solution, removal occurs before trying another possibility. This algorithm continues until filling out the entire board correctly or exhausting possibilities when returning failure status upward along recursive calls stack frames. --related questions-- 1. How does constraint propagation improve efficiency while solving puzzles like Sudoku? 2. Can genetic algorithms provide alternative methods for tackling similar combinatorial problems effectively? 3. What optimizations could enhance performance further beyond basic DFS/backtracking techniques used here?
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