You have a set of jobs, each with a deadline and a profit (or cost) associated with completing it within its deadline. The objective is to find the sequence of jobs that maximizes total profit or minimizes total cost.

Each job takes a unit of time to complete. One job can be scheduled at a time. Jobs have specific deadlines and associated profits or penalties.

Greedy Algorithm: One of the most common approaches is using a greedy algorithm, where jobs are prioritized based on their profit or deadline. The algorithm selects the job that offers the most benefit (highest profit or lowest penalty) first.

Sorting: Jobs are often sorted based on their profit or deadline as part of the algorithm.

Feasibility Check: After sorting, each job is checked for feasibility, i.e., whether it can be completed within its deadline.

The computational complexity of the problem can vary depending on the approach used. The greedy method often provides an efficient solution but doesn't always guarantee the optimal sequence.

This problem is relevant in various scenarios like manufacturing, scheduling in computer systems, and project management, where tasks need to be completed optimally to achieve maximum efficiency or profit.