給定 m×n 非負整數矩陣,從左上角走到右下角,每步只能向右或向下,求路徑上數字和的最小值。
dp[i][j]:走到 (i,j) 的最小路徑和。
轉移:dp[i][j] = min(dp[i-1][j], dp[i][j-1]) + grid[i][j]
邊界:首行只能從左來,首列只能從上來。
class Solution {
public:
int minPathSum(vector>& grid) {
int m = grid.size(), n = grid[0].size();
vector> dp(m, vector(n));
dp[0][0] = grid[0][0];
for (int i = 1; i < m; ++i) dp[i][0] = dp[i-1][0] + grid[i][0];
for (int j = 1; j < n; ++j) dp[0][j] = dp[0][j-1] + grid[0][j];
for (int i = 1; i < m; ++i)
for (int j = 1; j < n; ++j)
dp[i][j] = min(dp[i-1][j], dp[i][j-1]) + grid[i][j];
return dp[m-1][n-1];
}
};
public class Solution {
public int minPathSum(int[][] grid) {
int m = grid.length, n = grid[0].length;
int[][] dp = new int[m][n];
dp[0][0] = grid[0][0];
for (int i = 1; i < m; ++i) dp[i][0] = dp[i-1][0] + grid[i][0];
for (int j = 1; j < n; ++j) dp[0][j] = dp[0][j-1] + grid[0][j];
for (int i = 1; i < m; ++i)
for (int j = 1; j < n; ++j)
dp[i][j] = Math.min(dp[i-1][j], dp[i][j-1]) + grid[i][j];
return dp[m-1][n-1];
}
}
class Solution:
def minPathSum(self, grid: List[List[int]]) -> int:
m, n = len(grid), len(grid[0])
dp = [[0]*n for _ in range(m)]
dp[0][0] = grid[0][0]
for i in range(1, m): dp[i][0] = dp[i-1][0] + grid[i][0]
for j in range(1, n): dp[0][j] = dp[0][j-1] + grid[0][j]
for i in range(1, m):
for j in range(1, n):
dp[i][j] = min(dp[i-1][j], dp[i][j-1]) + grid[i][j]
return dp[-1][-1]
dp[n]:逐行更新,dp[j] = min(dp[j], dp[j-1]) + grid[i][j]。grid:grid[i][j] += min(grid[i-1][j], grid[i][j-1]),無額外空間(若允許修改輸入)。最小路徑和是二維 DP 入門必修題。狀態定義直觀、轉移方程對稱、邊界處理簡單。面試時寫出二維版講清邏輯,再現場優化至一維或原地修改,展示空間優化技巧。可延伸至「帶障礙物」、「三方向移動」、「路徑計數」等變體。