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Machines can have sequence-dependent setups. Objective function can be to minimize the makespan, the L p norm, tardiness, maximum lateness etc. It can also be multi-objective optimization problem. 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 ...
The presence of the job characteristic is implicitly assumed and not denoted in the problem name, unless there are some restrictions as for example =, assuming that all due dates are equal to some given date. ¯: for each job a strict deadline is given. Every job must complete before its deadline.
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 ...
In settings with deadlines, it is possible that, if the job is completed by the deadline, there is a profit p j. Otherwise, there is no profit. The goal is to maximize the profit. Single-machine scheduling with deadlines is NP-hard; Sahni [3] presents both exact exponential-time algorithms and a polynomial-time approximation algorithm.
To speed up the deadline search within the ready queue, the queue entries be sorted according to their deadlines. When a new process or a periodic process is given a new deadline, it is inserted before the first process with a later deadline. This way, the processes with the earliest deadlines are always at the beginning of the queue.
Job times must be independent of the job sequence. All jobs must be processed in the first work center before going through the second work center. All jobs are equally prioritised. Johnson's rule is as follows: List the jobs and their times at each work center. Select the job with the shortest activity time. If that activity time is for the ...
Lawler's algorithm is an efficient algorithm for solving a variety of constrained scheduling problems, particularly single-machine scheduling. [1] It can handle precedence constraints between jobs, requiring certain jobs to be completed before other jobs can be started.
In realtime scheduling algorithms for periodic jobs, an acceptance test is needed before accepting a sporadic job with a hard deadline. One of the simplest acceptance tests for a sporadic job is calculating the amount of slack time between the release time and deadline of the job.