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1681. Minimum Incompatibility

Description

You are given an integer array nums​​​ and an integer k. You are asked to distribute this array into k subsets of equal size such that there are no two equal elements in the same subset.

A subset's incompatibility is the difference between the maximum and minimum elements in that array.

Return the minimum possible sum of incompatibilities of the k subsets after distributing the array optimally, or return -1 if it is not possible.

A subset is a group integers that appear in the array with no particular order.

 

Example 1:

Input: nums = [1,2,1,4], k = 2
Output: 4
Explanation: The optimal distribution of subsets is [1,2] and [1,4].
The incompatibility is (2-1) + (4-1) = 4.
Note that [1,1] and [2,4] would result in a smaller sum, but the first subset contains 2 equal elements.

Example 2:

Input: nums = [6,3,8,1,3,1,2,2], k = 4
Output: 6
Explanation: The optimal distribution of subsets is [1,2], [2,3], [6,8], and [1,3].
The incompatibility is (2-1) + (3-2) + (8-6) + (3-1) = 6.

Example 3:

Input: nums = [5,3,3,6,3,3], k = 3
Output: -1
Explanation: It is impossible to distribute nums into 3 subsets where no two elements are equal in the same subset.

 

Constraints:

  • 1 <= k <= nums.length <= 16
  • nums.length is divisible by k
  • 1 <= nums[i] <= nums.length

Solutions

Solution 1: Preprocessing + State Compression + Dynamic Programming

Let's assume that the size of each subset after partitioning is $m$, so $m=\frac{n}{k}$, where $n$ is the length of the array.

We can enumerate all subsets $i$, where $i \in [0, 2^n)$, if the binary representation of subset $i$ has $m$ ones, and the elements in subset $i$ are not repeated, then we can calculate the incompatibility of subset $i$, denoted as $g[i]$, i.e., $g[i]=\max_{j \in i} {nums[j]} - \min_{j \in i} {nums[j]}$.

Next, we can use dynamic programming to solve.

We define $f[i]$ as the minimum sum of incompatibilities when the current partitioned subset state is $i$. Initially, $f[0]=0$, which means no elements are partitioned into the subset, and the rest $f[i]=+\infty$.

For state $i$, we find all undivided and non-repeated elements, represented by a state $mask$. If the number of elements in state $mask$ is greater than or equal to $m$, then we enumerate all subsets $j$ of $mask$, and satisfy $j \subset mask$, then $f[i \cup j]=\min {f[i \cup j], f[i]+g[j]}$.

Finally, if $f[2^n-1]=+\infty$, it means that it cannot be partitioned into $k$ subsets, return $-1$, otherwise return $f[2^n-1]$.

The time complexity is $O(3^n)$, and the space complexity is $O(2^n)$. Here, $n$ is the length of the array.

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class Solution:
    def minimumIncompatibility(self, nums: List[int], k: int) -> int:
        n = len(nums)
        m = n // k
        g = [-1] * (1 << n)
        for i in range(1, 1 << n):
            if i.bit_count() != m:
                continue
            s = set()
            mi, mx = 20, 0
            for j, x in enumerate(nums):
                if i >> j & 1:
                    if x in s:
                        break
                    s.add(x)
                    mi = min(mi, x)
                    mx = max(mx, x)
            if len(s) == m:
                g[i] = mx - mi
        f = [inf] * (1 << n)
        f[0] = 0
        for i in range(1 << n):
            if f[i] == inf:
                continue
            s = set()
            mask = 0
            for j, x in enumerate(nums):
                if (i >> j & 1) == 0 and x not in s:
                    s.add(x)
                    mask |= 1 << j
            if len(s) < m:
                continue
            j = mask
            while j:
                if g[j] != -1:
                    f[i | j] = min(f[i | j], f[i] + g[j])
                j = (j - 1) & mask
        return f[-1] if f[-1] != inf else -1

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class Solution {
    public int minimumIncompatibility(int[] nums, int k) {
        int n = nums.length;
        int m = n / k;
        int[] g = new int[1 << n];
        Arrays.fill(g, -1);
        for (int i = 1; i < 1 << n; ++i) {
            if (Integer.bitCount(i) != m) {
                continue;
            }
            Set<Integer> s = new HashSet<>();
            int mi = 20, mx = 0;
            for (int j = 0; j < n; ++j) {
                if ((i >> j & 1) == 1) {
                    if (!s.add(nums[j])) {
                        break;
                    }
                    mi = Math.min(mi, nums[j]);
                    mx = Math.max(mx, nums[j]);
                }
            }
            if (s