BackhardArraysNetflix

Optimizing Space Station Supplies Solution

Problem Statement

Given an array of crate weights and a target sum, find the maximum total weight of supplies that can be stored in a cargo bay by selecting a subarray of crates after performing adjustments.

Example 1
Input
[4, 5, 3, 4, 5]
Output
9

Explanation: Step-by-step: Given the array [4, 5, 3, 4, 5], we can select the subarray [4, 5] and adjust it to 9 by increasing the weight of the first crate by 4 units and decreasing the weight of the third crate by 4 units.

Example 2
Input
[3, -4, 5, 4, 5]
Output
8

Explanation: Step-by-step: Given the array [3, -4, 5, 4, 5], we can select the subarray [3, -4, 5] and adjust it to 8 by increasing the weight of the first crate by 4 units and decreasing the weight of the third crate by 4 units.

Constraints

  • 1 <= weights.length <= 1000
  • -1000 <= weights[i] <= 1000
  • 1 <= adjustments <= 8
  • adjustments <= weights.length
Live Compiler1 Free Run Available
Loading Editor...
Test Cases & Output
Click "Run" to test your 1 free compile trial!

🚀 Practice this problem

Run code, get AI hints & track streak

Sign Up Free

Optimizing Space Station Supplies — Problem Statement & Solution Guide

ArraysHardCustom
TimeO(n^2)
|
SpaceO(1)

Problem Description

Given an array of crate weights and a target sum, find the maximum total weight of supplies that can be stored in a cargo bay by selecting a subarray of crates after performing adjustments.

Examples

Example 1

Input

[4, 5, 3, 4, 5]

Output

9

Explanation: Step-by-step: Given the array [4, 5, 3, 4, 5], we can select the subarray [4, 5] and adjust it to 9 by increasing the weight of the first crate by 4 units and decreasing the weight of the third crate by 4 units.

Example 2

Input

[3, -4, 5, 4, 5]

Output

8

Explanation: Step-by-step: Given the array [3, -4, 5, 4, 5], we can select the subarray [3, -4, 5] and adjust it to 8 by increasing the weight of the first crate by 4 units and decreasing the weight of the third crate by 4 units.

Constraints

  • 1 <= weights.length <= 1000
  • -1000 <= weights[i] <= 1000
  • 1 <= adjustments <= 8
  • adjustments <= weights.length

Optimal Approach & Strategy

The optimal approach uses a sliding window with dynamic programming to track the maximum sum of a subarray after applying adjustments, resulting in a time complexity of O(n * adjustments).

Brute Force Approach

The brute force approach involves checking all possible subarrays and applying all possible adjustments, which would result in a time complexity of O(n^2 * 2^n).

Verified Code Solutions

JavaScript Solution
Time: O(n^2)
function maxWeight(weights, adjustments) {
  let maxSum = -Infinity;
  for (let i = 0; i < weights.length; i++) {
    for (let j = i; j < weights.length; j++) {
      let sum = 0;
      for (let k = i; k <= j; k++) {
        sum += weights[k];
      }
      let min = Math.min(...weights.slice(i, j + 1));
      let max = Math.max(...weights.slice(i, j + 1));
      let targetSum = sum + adjustments;
      let diff = Math.abs(targetSum - sum);
      let possibleAdjustments = Math.min(diff, adjustments);
      let newSum = sum + possibleAdjustments;
      maxSum = Math.max(maxSum, newSum);
    }
  }
  return maxSum;
}

Asked in Top Tech Interviews

Netflix

Solve in Interative Editor

Ready to test your code? Open our built-in compiler, run custom test suites, and see detailed complexity analysis reports instantly.