You are given a 0-indexed m x n
integer matrix grid
consisting of distinct integers from 0
to m * n - 1
. You can move in this matrix from a cell to any other cell in the next row. That is, if you are in cell (x, y)
such that x < m - 1
, you can move to any of the cells (x + 1, 0)
, (x + 1, 1)
, ..., (x + 1, n - 1)
. Note that it is not possible to move from cells in the last row.
Each possible move has a cost given by a 0-indexed 2D array moveCost
of size (m * n) x n
, where moveCost[i][j]
is the cost of moving from a cell with value i
to a cell in column j
of the next row. The cost of moving from cells in the last row of grid
can be ignored.
The cost of a path in grid
is the sum of all values of cells visited plus the sum of costs of all the moves made. Return the minimum cost of a path that starts from any cell in the first row and ends at any cell in the last row.
Example 1:
Input: grid = [[5,3],[4,0],[2,1]], moveCost = [[9,8],[1,5],[10,12],[18,6],[2,4],[14,3]] Output: 17 Explanation: The path with the minimum possible cost is the path 5 -> 0 -> 1. - The sum of the values of cells visited is 5 + 0 + 1 = 6. - The cost of moving from 5 to 0 is 3. - The cost of moving from 0 to 1 is 8. So the total cost of the path is 6 + 3 + 8 = 17.
Example 2:
Input: grid = [[5,1,2],[4,0,3]], moveCost = [[12,10,15],[20,23,8],[21,7,1],[8,1,13],[9,10,25],[5,3,2]] Output: 6 Explanation: The path with the minimum possible cost is the path 2 -> 3. - The sum of the values of cells visited is 2 + 3 = 5. - The cost of moving from 2 to 3 is 1. So the total cost of this path is 5 + 1 = 6.
Constraints:
m == grid.length
n == grid[i].length
2 <= m, n <= 50
grid
consists of distinct integers from0
tom * n - 1
.moveCost.length == m * n
moveCost[i].length == n
1 <= moveCost[i][j] <= 100
Companies: Google
Related Topics:
Array, Dynamic Programming, Matrix
Similar Questions:
- Unique Paths (Medium)
- Unique Paths II (Medium)
- Minimum Path Sum (Medium)
- Dungeon Game (Hard)
- Paint House (Medium)
// OJ: https://leetcode.com/problems/minimum-path-cost-in-a-grid
// Author: github.com/lzl124631x
// Time: O(MN^2)
// Space: O(MN)
class Solution {
public:
int minPathCost(vector<vector<int>>& A, vector<vector<int>>& C) {
int M = A.size(), N = A[0].size(), ans = INT_MAX;
vector<vector<int>> dp(M, vector<int>(N, INT_MAX));
for (int j = 0; j < N; ++j) dp[M - 1][j] = A[M - 1][j];
for (int i = M - 2; i >= 0; --i) {
for (int j = 0; j < N; ++j) {
for (int k = 0; k < N; ++k) {
dp[i][j] = min(dp[i][j], dp[i + 1][k] + A[i][j] + C[A[i][j]][k]);
}
if (i == 0) ans = min(ans, dp[i][j]);
}
}
return ans;
}
};
// OJ: https://leetcode.com/problems/minimum-path-cost-in-a-grid
// Author: github.com/lzl124631x
// Time: O(MN^2)
// Space: O(N) if we are not allowed to compute values in-place
class Solution {
public:
int minPathCost(vector<vector<int>>& A, vector<vector<int>>& C) {
int M = A.size(), N = A[0].size(), ans = INT_MAX;
for (int i = M - 2; i >= 0; --i) {
for (int j = 0; j < N; ++j) {
int mn = INT_MAX;
for (int k = 0; k < N; ++k) {
mn = min(mn, A[i + 1][k] + C[A[i][j]][k]);
}
A[i][j] += mn;
if (i == 0) ans = min(ans, A[i][j]);
}
}
return ans;
}
};