Competitive ProgrammingEasy

Minimum time to finish jobs

Detailed guide and Python implementation for the 'Minimum time to finish jobs' problem.

Problem Statement

Easy

Write a function min_time_jobs(jobs, k, t) that finds the minimum time to finish all jobs. The array jobs represents the time required to complete each job. There are k assignees, and each assignee takes t units of time to complete 1 unit of job. Jobs can only be assigned as contiguous sub-segments to the assignees.

Constraints
  • 1 <= len(jobs) <= 10^5
  • 1 <= k <= len(jobs)
  • 1 <= t <= 1000
  • 1 <= jobs[i] <= 10^4

Examples

Example 1
Input
min_time_jobs([10, 7, 8, 12, 8, 5, 9], 4, 5)
Output
100
Explanation

Optimal contiguous assignment: [10, 7], [8, 12], [8, 5], [9]. Max job units assigned is 20 (8+12). Time = 20 * 5 = 100.

Example 2
Input
min_time_jobs([4, 5, 10], 2, 1)
Output
10
Explanation

Optimal contiguous assignment: [4, 5], [10]. Max job units assigned is 10. Time = 10 * 1 = 10.

Need a Hint?
Consider using Greedy-specific data structures like sets or heaps.
Edge Cases to Watch
  • Empty input structures
  • Single element inputs
  • Large numerical bounds

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