Imagine you're a project manager at a tech company with k developers on your team. You have a list of jobs where each jobs[i] represents the time (in hours) needed to complete the i-th task.
Your challenge is to distribute these jobs among your developers such that no single developer is overloaded. Each job must be assigned to exactly one developer, and a developer's workload is the sum of all job times assigned to them.
Goal: Find the optimal job assignment that minimizes the maximum workload of any developer. This ensures fair work distribution and project completion in minimum time.
Input: An array jobs of positive integers and an integer k (number of workers)
Output: The minimum possible maximum working time across all workers
Input & Output
Visualization
Time & Space Complexity
Each job can be assigned to any of k workers, leading to k^n total assignments
Space needed to store current assignment and worker workloads
Constraints
- 1 โค k โค jobs.length โค 12
- 1 โค jobs[i] โค 107
- Small input size allows for backtracking solutions