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Shortest job next being executed. Shortest job next (SJN), also known as shortest job first (SJF) or shortest process next (SPN), is a scheduling policy that selects for execution the waiting process with the smallest execution time. [1] SJN is a non-preemptive algorithm. Shortest remaining time is a preemptive variant of SJN.
The time that machine i needs in order to process job j is denoted by p i,j. In the general case, the times p i,j are unrelated, and any matrix of positive processing times is possible. In the specific variant called uniform machine scheduling , some machines are uniformly faster than others.
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 ...
Shortest remaining time being executed. Shortest remaining time, also known as shortest remaining time first (SRTF), is a scheduling method that is a preemptive version of shortest job next scheduling. In this scheduling algorithm, the process with the smallest amount of time remaining until completion is selected to execute. Since the ...
Jobs may have constraints, for example a job i needs to finish before job j can be started (see workflow). Also, the objective function can be multi-criteria. [4] Set of jobs can relate to different set of machines. Deterministic (fixed) processing times or probabilistic processing times.
Single-machine scheduling or single-resource scheduling or Dhinchak Pooja is an optimization problem in computer science and operations research.We are given n jobs J 1, J 2, ..., J n of varying processing times, which need to be scheduled on a single machine, in a way that optimizes a certain objective, such as the throughput.
Longest-processing-time-first (LPT) is a greedy algorithm for job scheduling. The input to the algorithm is a set of jobs, each of which has a specific processing-time. There is also a number m specifying the number of machines that can process the jobs. The LPT algorithm works as follows:
The open-shop scheduling problem can be solved in polynomial time for instances that have only two workstations or only two jobs. It may also be solved in polynomial time when all nonzero processing times are equal: in this case the problem becomes equivalent to edge coloring a bipartite graph that has the jobs and workstations as its vertices, and that has an edge for every job-workstation ...