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Problem: Schedule Tasks on Minimum Machines

Medium
30 min
Explore scheduling tasks on machines where no overlap is allowed using heap data structures. Understand how to find the minimum machines needed to complete all tasks efficiently. This lesson helps you improve problem-solving skills for coding interviews by applying heaps to dynamic scheduling challenges.

Statement

We are given an input array, tasks, where tasks[i] =[starti,endi]= [start_i, end_i] represents the start and end times of nn tasks. Our goal is to schedule these tasks on machines given the following criteria:

  1. A machine can execute only one task at a time.

  2. A machine can begin executing a new task immediately after completing the previous one.

  3. An unlimited number of machines are available.

Find the minimum number of machines required to complete these nn tasks.

Constraints:

  • n==n == tasks.length

  • 11 \leq tasks.length 103\leq 10^3

  • 00 \leq tasksi.start << tasksi.end 104\leq 10^4

Problem
Ask
Submissions

Problem: Schedule Tasks on Minimum Machines

Medium
30 min
Explore scheduling tasks on machines where no overlap is allowed using heap data structures. Understand how to find the minimum machines needed to complete all tasks efficiently. This lesson helps you improve problem-solving skills for coding interviews by applying heaps to dynamic scheduling challenges.

Statement

We are given an input array, tasks, where tasks[i] =[starti,endi]= [start_i, end_i] represents the start and end times of nn tasks. Our goal is to schedule these tasks on machines given the following criteria:

  1. A machine can execute only one task at a time.

  2. A machine can begin executing a new task immediately after completing the previous one.

  3. An unlimited number of machines are available.

Find the minimum number of machines required to complete these nn tasks.

Constraints:

  • n==n == tasks.length

  • 11 \leq tasks.length 103\leq 10^3

  • 00 \leq tasksi.start << tasksi.end 104\leq 10^4