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Problem · Array

Minimize Variation

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As an operations engineer at Amazon, you are responsible for organizing the distribution of n different items in the warehouse. The size of each product is provided in an array productSize, where productSize[i] represents the size of the ith product.

You construct a new array called variation, where each element variation[i] is the difference between the largest and smallest product sizes among the first i products. Mathematically, this is defined as:

variation[i] = max(productSize[1], productSize[2], ..., productSize[i]) - min(productSize[1], productSize[2], ..., productSize[i])

Your goal is to arrange the products in a way that minimizes the total variation, i.e., the sum of variation[1] + variation[2] + ... + variation[n]. Determine the minimum possible value of this sum after you have reordered the products.

Function Description

Complete the function minimizeVariation in the editor.

My deepest thanks to the incredible friend who helped bring the problem to completion. 🐳

Examples

01 · Example 1

productSize = [3, 1, 2]
return = 3

By reordering the products as productSize = [2,3,1]:

variation[0] = max(2) - min(2) = 2-2 = 0.
variation[1] = max(2,3) - min(2,3) = 3-2 = 1.
variation[2] = max(2,3,1) - min(2,3,1) = 3-1 = 2.

The sum is variation[0] + variation[1] + variation[2] = 0+1+2 = 3. This is the minimum possible total variation after rearranging.

02 · Example 2

productSize = [6, 1, 4, 2]
return = 9

By reordering the products as productSize = [1,2,4,6]:

variation[0] = max(1) - min(1) = 1-1 = 0.
variation[1] = max(1,2) - min(1,2) = 2-1 = 1.
variation[2] = max(1,2,4) - min(1,2,4) = 4-1 = 3.
variation[3] = max(1,2,4,6) - min(1,2,4,6) = 6-1 = 5.

The minimum total variation is variation[0] + variation[1] + variation[2] + variation[3] = 0+1+3+5 = 9.

03 · Example 3

productSize = [4, 5, 4, 2, 6, 1, 1]
return = 16

By reordering the products as productSize = [1, 1, 2, 4, 4, 5, 6]: variation[0] = max(1) - min(1) = 1 - 1 = 0 variation[1] = max(1,1) - min(1,1) = 1 - 1 = 0 variation[2] = max(1,1,2) - min(1,1,2) = 2 - 1 = 1 variation[3] = max(1,1,2,4) - min(1,1,2,4) = 4 - 1 = 3 variation[4] = max(1,1,2,4,4) - min(1,1,2,4,4) = 4 - 1 = 3 variation[5] = max(1,1,2,4,4,5) - min(1,1,2,4,4,5) = 5 - 1 = 4 variation[6] = max(1,1,2,4,4,5,6) - min(1,1,2,4,4,5,6) = 6 - 1 = 5 variation[0] + variation[1] + variation[2] + variation[3] + variation[4] + variation[5] + variation[6] = 0 + 0 + 1 + 3 + 3 + 4 + 5 = 16 This test case example was added on Jun 25, 2025. Relevant source image was included in the Problem Source section below. If you notice anything wrong, you are more than welcome to lmk! Many thanks in advance!

04 · Example 4

productSize = [6, 1, 4, 2]
return = 9

By reordering the products as productSize = [1, 2, 4, 6]: variation[0] = max(1) - min(1) = 1 - 1 = 0 variation[1] = max(1,2) - min(1,2) = 2 - 1 = 1 variation[2] = max(1,2,4) - min(1,2,4) = 4 - 1 = 3 variation[3] = max(1,2,4,6) - min(1,2,4,6) = 6 - 1 = 5 variation[0] + variation[1] + variation[2] + variation[3] = 0 + 1 + 3 + 5 = 9 This test case example was added on Jun 25, 2025. Relevant source image was included in the Problem Source section below. If you notice anything wrong, you are more than welcome to lmk! Many thanks in advance!

05 · Example 5

productSize = [3, 1, 3, 3, 6, 6]
return = 11

Try: sorting based frequency [3, 3, 3, 6, 6, 1] "I" Subarray Max Min Variation 0 [3] 3 3 0 1 [3, 3] 3 3 0 2 [3, 3, 3] 3 3 0 3 [3, 3, 3, 6] 6 3 3 4 [3, 3, 3, 6, 6] 6 3 3 5 [3, 3, 3, 6, 6,1] 6 1 5 Total = 0 + 0 + 0 + 3 + 3 + 5 = 11 The original OP mentioned this case failed, though it's unclear whether they meant the case itself was incorrect or that they failed to pass it. So, use it with caution! This test case example was added on Jun 25, 2025. Relevant source image was included in the Problem Source section below. If you notice anything wrong, you are more than welcome to lmk! Many thanks in advance!

Constraints

1 <= n <= 2000

1 <= productSize[i] <= 10^9

Complete constraints set was added on 06-22-2025 :)