Topic
Single-machine scheduling
About: Single-machine scheduling is a research topic. Over the lifetime, 2473 publications have been published within this topic receiving 56288 citations.
Papers published on a yearly basis
Papers
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TL;DR: In this paper, a new dispatching rule is developed to minimize the total tool setup time, and the performance of the proposed rule was tested against three priority rules: first-in-first-out, shortest processing time and longest processing time.
31 citations
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TL;DR: This paper presents a single machine scheduling problem with sequence dependent changeover times, an optimizing solution procedure and various appropriate heuristics are reviewed, and it is demonstrated that the best heuristic for the static problem is not necessarily thebest heuristic in the dynamic situation.
Abstract: This paper presents a single machine scheduling problem with sequence dependent changeover times. An optimizing solution procedure and various appropriate heuristics are reviewed. We then go on to consider the performance of these and other heuristics in the dynamic situation, as new jobs arrive to be processed and have to be added into the existing schedule at some time. Clearly an ideal solution would be to reschedule as each new job arrived, but as this is not generally practical from a computational viewpoint, it has to be carried out less frequently. The actual frequency of this rescheduling is clearly of importance, and some of the heuristics are more adaptable to this than others. Some results are presented which attempt to quantify this adaptability for the heuristics in question, and it is demonstrated that the best heuristic for the static problem is not necessarily the best heuristic in the dynamic situation.
31 citations
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TL;DR: An efficient branch-and-bound algorithm is presented that fully exploits the principle of optimality in a scheduling problem in which n jobs with distinct deadlines are to be scheduled on a single machine.
31 citations
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TL;DR: The problem is NP-complete in the ordinary sense and a dynamic programming based pseudo-polynomial algorithm is developed that minimizes the weighted number of early and tardy jobs and the location penalty.
Abstract: This paper studies a single machine scheduling problem to minimize the weighted number of early and tardy jobs with a common due window. There are n non-preemptive and simultaneously available jobs. Each job will incur an early (tardy) penalty if it is early (tardy) with respect to the common due window under a given schedule. The window size is a given parameter but the window location is a decision variable. The objective of the problem is to find a schedule that minimizes the weighted number of early and tardy jobs and the location penalty. We show that the problem is NP-complete in the ordinary sense and develop a dynamic programming based pseudo-polynomial algorithm. We conduct computational experiments, the results of which show that the performance of the dynamic algorithm is very good in terms of memory requirement and CPU time. We also provide polynomial time algorithms for two special cases.
31 citations
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TL;DR: This paper shows that the main results in a recent paper by Zhang and Yan are incorrect as an important reason is missing, that is, the processing time of a job is variable according to a general learning effect, and gives a revised model with a generallearning effect.
31 citations