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Optimal job scheduling is a class of optimization problems related to scheduling. The inputs to such problems are a list of jobs (also called processes or tasks) and a list of machines (also called processors or workers). The required output is a schedule – an assignment of jobs to machines. The schedule should optimize a certain objective ...
The variant where variables are required to be 0 or 1, called zero-one linear programming, and several other variants are also NP-complete [2] [3]: MP1 Some problems related to Job-shop scheduling; Knapsack problem, quadratic knapsack problem, and several variants [2] [3]: MP9 Some problems related to Multiprocessor scheduling
Least slack time (LST) scheduling is an algorithm for dynamic priority scheduling. It assigns priorities to processes based on their slack time. Slack time is the amount of time left after a job if the job was started now. This algorithm is also known as least laxity first.
Interval scheduling is a class of problems in computer science, particularly in the area of algorithm design. The problems consider a set of tasks. The problems consider a set of tasks. Each task is represented by an interval describing the time in which it needs to be processed by some machine (or, equivalently, scheduled on some resource).
Unrelated-machines scheduling is an optimization problem in computer science and operations research. It is a variant of optimal job scheduling . We need to schedule n jobs J 1 , J 2 , ..., J n on m different machines, such that a certain objective function is optimized (usually, the makespan should be minimized).
Flow Shop Ordonnancement. Flow-shop scheduling is an optimization problem in computer science and operations research.It is a variant of optimal job scheduling.In a general job-scheduling problem, we are given n jobs J 1, J 2, ..., J n of varying processing times, which need to be scheduled on m machines with varying processing power, while trying to minimize the makespan – the total length ...
Earliest deadline first (EDF) or least time to go is a dynamic priority scheduling algorithm used in real-time operating systems to place processes in a priority queue. Whenever a scheduling event occurs (task finishes, new task released, etc.) the queue will be searched for the process closest to its deadline.
This is a sub-category of Category:Scheduling algorithms, focusing on heuristic algorithms for scheduling tasks (jobs) to processors (machines). For optimization problems related to scheduling, see Category:Optimal scheduling.