LeetCode 3077: Maximum Strength of K Disjoint Subarrays Solution
Master LeetCode problem 3077 (Maximum Strength of K Disjoint Subarrays), a hard challenge, with our optimized solutions in Java, C++, and Python. Explore detailed explanations, test your code in our interactive editor, and prepare for coding interviews.
3077. Maximum Strength of K Disjoint Subarrays
Problem Explanation
Explanation:
To solve this problem, we can use dynamic programming. We will create a 3D dp array where dp[i][j][l] represents the maximum strength that can be obtained by selecting j disjoint subarrays from the first i elements of the input array, where the l-th subarray ends at index i.
At each index i, we can either start a new subarray or extend an existing subarray. The maximum strength can be calculated based on these two choices.
The time complexity of this solution is O(nk^2) where n is the length of the input array and k is the number of disjoint subarrays to select. The space complexity is O(nk) for the dp array.
:
Solution Code
class Solution {
public int maxStrength(int[] nums, int k) {
int n = nums.length;
int[][][] dp = new int[n + 1][k + 1][k + 1];
for (int i = 1; i <= n; i++) {
for (int j = 1; j <= k; j++) {
for (int l = 0; l <= k; l++) {
dp[i][j][l] = Math.max(dp[i][j][l], dp[i - 1][j][l]);
if (l > 0) {
dp[i][j][l] = Math.max(dp[i][j][l], dp[i - 1][j - 1][l - 1] + nums[i - 1]);
}
}
}
}
int maxStrength = 0;
for (int l = 0; l <= k; l++) {
maxStrength = Math.max(maxStrength, dp[n][k][l]);
}
return maxStrength;
}
}Try It Yourself
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