Longest Divisible Subset | (DP-44)


Problem Link: Divisible Set

Let us first understand the difference between subset and subsequence.

In a subsequence, the elements need to follow the order of the original array whereas in a subset there is no constraint on the order of the elements. 

Divisible Subset

A divisible subset is the one in which if we pick two elements i and j from the subset, then either arr[i]%arr[j] == 0 or arr[j] % arr[i] == 0. For example, [16,8,4] is a divisible subset.

Given an array with distinct elements, we need to print its longest divisible subset. We can print any answer.



As here we are finding the subsets, we can change the order of the original array. Let us sort it out first.

Now, we can start thinking in terms of subsequences questions solved earlier.

Let us pick the first index element in an array (say temp) and move to the next index.

Now, i = 1 and arr[i] = 4. We can again push this into the array as 4%1 == 0.

For i=2, arr[i] = 7. We can’t push it in the temp array as 7%4 != 0 . Now, i = 3 and arr[i] = 8. We can again push this into the array as 8%4 == 0. 

Now as the elements in the temp array were sorted, we only checked that element 8 was divisible by the last element of the tamp array i.e 4. But we know that 4 is divisible by the first element of the temp array i.e 4%1 == 0. As the array is sorted and 8%4 == 0. And 4%1==0. We can automatically imply that 8%1==0. Hence this temp array formed is a divisible subsequence.

Let us take another case to make it more clear.

As i = 4, arr[i] = 16. Now 16 is divisible by the last element of the temp array which is 8, so we can push 16 into the temp array.

To summarize:

  • Whenever the current index element (arr[i]) is divisible by the last element of the temp array(say temp[last]), we can push that element to the temp array.
  • As the temp array formed will always be sorted, and arr[i] is divisible by the temp[last], we can say that arr[i] will be divisible by every element before the temp[last] of the temp array.
  • Therefore, this temp array will be a divisible subsequence and we just need to find the longest divisible subsequence of the array. 


The algorithm approach is stated as follows:

  • First of all sort the array,
  • Then find the longest divisible subsequence of the array.
  • In order to find the longest divisible subsequence, we will follow the algorithm used to find the longest increasing subsequence discussed in the/** link to dp-42 **/.
  • The distinguishing factor between longest increasing subsequence and longest divisible subsequence is that we used to insert the element if arr[i] > arr[prev] but here we will insert the element when arr[i] % arr[prev] == 0.
  • At last return the hash array as the answer.


C++ Code

using namespace std;

vector<int> divisibleSet(vector<int>& arr){

    int n = arr.size();
    //sort the array
    sort(arr.begin(), arr.end());

    vector<int> dp(n,1);
    vector<int> hash(n,1);
    for(int i=0; i<=n-1; i++){
        hash[i] = i; // initializing with current index
        for(int prev_index = 0; prev_index <=i-1; prev_index ++){
            if(arr[i]%arr[prev_index] == 0 && 1 + dp[prev_index] > dp[i]){
                dp[i] = 1 + dp[prev_index];
                hash[i] = prev_index;
    int ans = -1;
    int lastIndex =-1;
    for(int i=0; i<=n-1; i++){
        if(dp[i]> ans){
            ans = dp[i];
            lastIndex = i;
    vector<int> temp;
    while(hash[lastIndex] != lastIndex){ // till not reach the initialization value
        lastIndex = hash[lastIndex];
    // reverse the array 

    return temp;

int main() {
	vector<int> arr = {1,16,7,8,4};
	vector<int> ans = divisibleSet(arr);
	cout<<" The longest divisible subset elements are: ";
	for(int i=0; i<ans.size(); i++){
	    cout<<ans[i]<<" ";


 The longest divisible subset elements are: 1 4 8 16

Time Complexity: O(N*N)

Reason: There are two nested loops.

Space Complexity: O(N)

Reason: We are only using two rows of size n.

Special thanks to Anshuman Sharma for contributing to this article on takeUforward. If you also wish to share your knowledge with the takeUforward fam, please check out this articleIf you want to suggest any improvement/correction in this article please mail us at [email protected]