How do you solve Assign Elements to Groups with Constraints on LeetCode?

Assign Elements to Groups with Constraints (LeetCode #3447) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n + m log m) time complexity and O(n) space complexity. Key insight: Using a sieve-like approach can significantly reduce the number of checks needed.

What is the time complexity of Assign Elements to Groups with Constraints?

The optimal solution for Assign Elements to Groups with Constraints runs in O(n + m log m) time and uses O(n) space. This complexity is due to iterating through elements and their multiples, which is much more efficient than checking each group against all elements.

What is the brute force solution for Assign Elements to Groups with Constraints?

The brute force approach for Assign Elements to Groups with Constraints is Brute Force, with O(n²) time complexity and O(1) space complexity. The brute force approach checks each group against all elements to find a suitable assignment. It simply iterates through every group and for each group, checks all elements to see if they can be assigned based on the divisibility condition. The optimal Optimal Solution approach improves this to O(n + m log m).

What algorithm or data structure is used to solve Assign Elements to Groups with Constraints?

Assign Elements to Groups with Constraints uses the following concepts: Array, Hash Table. The recommended patterns to study are: Hash Map, Array.

What are the interview tips for Assign Elements to Groups with Constraints?

Always consider edge cases, such as groups that cannot be assigned any elements. Explain your thought process clearly while coding to show your understanding. Practice similar problems to get comfortable with different approaches.

What are common mistakes when solving Assign Elements to Groups with Constraints?

Not checking if an element has already been assigned to a group. Assuming the order of elements matters when it does not.

#3447

Assign Elements to Groups with Constraints

Medium

ArrayHash TableHash MapArray

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(n + m log m)
Space	O(1)	O(n)

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Intuition

Time O(n + m log m)Space O(n)

The optimal solution uses a sieve-like approach to efficiently assign elements to groups. By iterating through each element and marking its multiples in the groups, we can directly assign the smallest index element that meets the divisibility condition.

⚙️

Algorithm

5 steps

1Step 1: Initialize an array 'assigned' with size equal to 'groups' and fill it with -1.
2Step 2: For each element in 'elements', iterate through its multiples up to the maximum value in 'groups'.
3Step 3: For each multiple, check if it is a valid group index and if it hasn't been assigned yet.
4Step 4: If valid, assign the index of the element to 'assigned' for that group.
5Step 5: Return the 'assigned' list.

solution.py9 lines

1def assign_elements(groups, elements):
2    assigned = [-1] * len(groups)
3    for j, element in enumerate(elements):
4        for multiple in range(element, max(groups) + 1, element):
5            if multiple in groups:
6                index = groups.index(multiple)
7                if assigned[index] == -1:
8                    assigned[index] = j
9    return assigned

ℹ

Complexity note: This complexity is due to iterating through elements and their multiples, which is much more efficient than checking each group against all elements.

1Using a sieve-like approach can significantly reduce the number of checks needed.
2Divisibility checks can be efficiently handled by iterating through multiples.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.