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Job-Dependent Due-Window Assignment Based On A Common Flow Allowance

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This article is published in Foundations of Computing and Decision Sciences.The article was published on 2010-01-01 and is currently open access. It has received 37 citations till now. The article focuses on the topics: Scheduling (computing).

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Citations
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Journal ArticleDOI

A survey on scheduling problems with due windows

TL;DR: A review of an extensive literature concerning problems with various models of given due windows, due window assignment andJob-independent and job-dependent earliness/tardiness penalties is presented, mentioning also their solution algorithms.
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Single-machine due-window assignment problem with learning effect and deteriorating jobs

TL;DR: In this article, the authors considered a single-machine common due-window assignment scheduling problem with learning effect and deteriorating jobs and showed that the problem remains polynomially solvable under the proposed model.
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Single-machine due window assignment and scheduling with a common flow allowance and controllable job processing time

TL;DR: Five versions of the problem are studied that differ in terms of the objective function and processing time function being used and structural properties of the optimal schedules and polynomial-time solution algorithms are provided.
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Scheduling a maintenance activity and due-window assignment based on common flow allowance

TL;DR: The problems based on all the combinations of these settings are shown to be solved in polynomial time and the set of potential optimal positions for the maintenance activity is fully characterized.
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Single-machine due-window assignment scheduling based on common flow allowance, learning effect and resource allocation

TL;DR: In this article, a single-machine due-window assignment scheduling problem based on a common flow allowance is considered, where the actual processing time of a job is a function of its position in a sequence (learning effect) and its continuously divisible and non-renewable resource allocation.
References
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Journal ArticleDOI

Single-machine scheduling with learning considerations

TL;DR: It is shown in this paper that even with the introduction of learning to job processing times two important types of single-machine problems remain polynomially solvable.
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A survey of the state-of-the-art of common due date assignment and scheduling research

TL;DR: A unified framework of the common due date assignment and scheduling problems in the deterministic case is provided by surveying the literature concerning the models involving single machine and parallel machines by finding an optimal value of thecommon due date and the related optimal schedule.
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Common Due Date Assignment to Minimize Total Penalty for the One Machine Scheduling Problem

TL;DR: A polynomial bound scheduling algorithm is presented for the solution of this problem along with the proof of optimality, a numerical example and discuss some extensions.
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Scheduling with general job-dependent learning curves

TL;DR: This work extends the setting studied so far to the case of job-dependent learning curves, that is, it allows the learning in the production process of some jobs to be faster than that of others, and shows that in the new, possibly more realistic setting, the problems of makespan and total flow-time minimization on a single machine, a due-date assignment problem and total flowspan on unrelated parallel machines remain polynomially solvable.
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Common due window size and location determination in a single machine scheduling problem

TL;DR: An O(n log n) algorithm is proposed to solve a single machine static and deterministic scheduling problem in which jobs have a common due window and the objective is to find the optimal size and location of the window as well as an optimal sequence to minimise a cost function.
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