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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).
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 ...
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.
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).
Parallel task scheduling (also called parallel job scheduling [1] [2] or parallel processing scheduling [3]) is an optimization problem in computer science and operations research. It is a variant of optimal job scheduling .
In this case, the available CPU cycles are divided first among the groups, then among the users within the groups, and then among the processes for that user. For example, if there are three groups (1,2,3) containing three, two, and four users respectively, the available CPU cycles will be distributed as follows: 100% / 3 groups = 33.3% per group
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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 ...