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Typical examples include job scheduling in manufacturing and data delivery scheduling in data processing networks. [1] In manufacturing environment, inventory management considers both tardiness and earliness undesirable. Tardiness involves backlog issues such as customer compensation for delays and loss of goodwill.
The modified due date scheduling is a scheduling heuristic created in 1982 by Baker and Bertrand, [1] used to solve the NP-hard single machine total-weighted tardiness problem. This problem is centered around reducing the global tardiness of a list of tasks which are characterized by their processing time, due date and weight by re-ordering them.
The algorithm builds the schedule back to front. For each scheduling step, it looks only at the tasks that no other tasks depend on, and puts the one with the latest due date at the end of the schedule queue. Then it repeats this process until all jobs are scheduled. The algorithm works by planning the job with the least impact as late as possible.
No wonder bosses say Gen Z are hard to manage: While 70% of boomers have zero tolerance for any level of tardiness, in Gen Z’s eyes, 10 minutes late is right on time.
In operations research, Johnson's rule is a method of scheduling jobs in two work centers. Its primary objective is to find an optimal sequence of jobs to reduce makespan (the total amount of time it takes to complete all jobs). It also reduces the amount of idle time between the two work centers. The method minimizes the makespan in the case ...
The project schedule is a calendar that links the tasks to be done with the resources that will do them. It is the core of the project plan used to show the organization how the work will be done, commit people to the project, determine resource needs, and used as a kind of checklist to make sure that every task necessary is performed.