LeetCode 1000. Minimum Cost to Merge Stones Solution in Java, C++, Python & Go | Explanation + Code

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1000. Minimum Cost to Merge Stones

Description

There are n piles of stones arranged in a row. The ith pile has stones[i] stones.

A move consists of merging exactly k consecutive piles into one pile, and the cost of this move is equal to the total number of stones in these k piles.

Return the minimum cost to merge all piles of stones into one pile. If it is impossible, return -1.

 

Example 1:

Input: stones = [3,2,4,1], k = 2
Output: 20
Explanation: We start with [3, 2, 4, 1].
We merge [3, 2] for a cost of 5, and we are left with [5, 4, 1].
We merge [4, 1] for a cost of 5, and we are left with [5, 5].
We merge [5, 5] for a cost of 10, and we are left with [10].
The total cost was 20, and this is the minimum possible.

Example 2:

Input: stones = [3,2,4,1], k = 3
Output: -1
Explanation: After any merge operation, there are 2 piles left, and we can't merge anymore.  So the task is impossible.

Example 3:

Input: stones = [3,5,1,2,6], k = 3
Output: 25
Explanation: We start with [3, 5, 1, 2, 6].
We merge [5, 1, 2] for a cost of 8, and we are left with [3, 8, 6].
We merge [3, 8, 6] for a cost of 17, and we are left with [17].
The total cost was 25, and this is the minimum possible.

 

Constraints:

  • n == stones.length
  • 1 <= n <= 30
  • 1 <= stones[i] <= 100
  • 2 <= k <= 30

Solutions

Solution 1

PythonJavaC++Go
class Solution: def mergeStones(self, stones: List[int], K: int) -> int: n = len(stones) if (n - 1) % (K - 1): return -1 s = list(accumulate(stones, initial=0)) f = [[[inf] * (K + 1) for _ in range(n + 1)] for _ in range(n + 1)] for i in range(1, n + 1): f[i][i][1] = 0 for l in range(2, n + 1): for i in range(1, n - l + 2): j = i + l - 1 for k in range(1, K + 1): for h in range(i, j): f[i][j][k] = min(f[i][j][k], f[i][h][1] + f[h + 1][j][k - 1]) f[i][j][1] = f[i][j][K] + s[j] - s[i - 1] return f[1][n][1](code-box)

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