Parallel machine scheduling with almost periodic maintenance and non-preemptive jobs to minimize makespan

Xu, Dehua; Sun, Kaibiao; Li, Hongxing

doi:10.1016/j.cor.2006.08.015

Cited by 84 publications

(26 citation statements)

References 10 publications

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“…Qi et al [35] proved that the maintenance scheduling on a single machine is NP-hard problem by reducing it to distance-constrained VRP (vehicle routing problem). Xu et al [49] modelled parallel machine scheduling with -almost periodic maintenance constraint, which means that the time between any two consecutive maintenance is within the interval ½T; T 0 , where T and T 0 are positive real numbers and T 0 À T\. Consequently, it can be concluded that the nature of the addressed problem in this paper is also NP-hard.…”

Section: Model Descriptionmentioning

confidence: 99%

Task scheduling system for UAV operations in indoor environment

Khosiawan

Park

Moon

et al. 2018

Neural Comput & Applic

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The application of unmanned aerial vehicle (UAV) in indoor environment is emerging nowadays due to the advancements in technology. UAV brings more space flexibility in an occupied or hardly accessible indoor environment, e.g. shop floor of manufacturing industry, greenhouse, and nuclear powerplant. UAV helps in creating an autonomous manufacturing system by executing tasks with less human intervention in a time-efficient manner. Consequently, a scheduler is an essential component to be focused on; yet the number of reported studies on UAV scheduling has been minimal. This work proposes a mathematical model of the problem and a heuristic-based methodology to solve it. To suit near real-time operations, a quick response towards uncertain events and a quick creation of new high-quality feasible schedule are needed. Hence, the proposed heuristic is incorporated with particle swarm optimization algorithm to find a near optimal schedule in a short computation time. This proposed methodology is implemented into a scheduler and tested on a few scales of datasets generated based on real flight demonstrations. Performance evaluation of scheduler is discussed in detail, and the best solution obtained from a selected set of parameters is reported.

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Section: Model Descriptionmentioning

confidence: 99%

Task scheduling system for UAV operations in indoor environment

Khosiawan

Park

Moon

et al. 2018

Neural Comput & Applic

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“…Although scheduling with machine maintenance has attracted many researchers' attentions in the last three decades, most of the past research mainly focuses on prefixed maintenance durations, see, e.g., Qi et al (1999), Liao and Chen (2003), Chen (2006aChen ( , b, 2008aChen ( , 2007aChen ( , b, 2009, Qi (2007), Sheen and Liao (2007), Ji et al (2007), Sbihi and Varnier (2008), Xu et al (2008Xu et al ( , 2009Xu et al ( , 2014, Sun and Li (2010), Xu and Yin (2011), Xu and Yang (2013), Shi and Xu (2014). However, as can be seen in many production systems, the time needed to perform a maintenance activity is not usually prefixed but depends on many factors such as the degree of tool wear, the amount of fuel to be filled, and the proficiency level of the maintenance workers.…”

Section: Introductionmentioning

confidence: 99%

Single-machine scheduling with preemptive jobs and workload-dependent maintenance durations

Zhao

2015

Oper Res Int J

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A single-machine scheduling problem with preemptive jobs and workload-dependent maintenance durations is considered. The length of a maintenance duration is modeled as an non-negative increasing function of the total processing time of the jobs scheduled between the current maintenance and the latest previous one. The objective is to minimize the makespan. Two optimal algorithms are proposed for the case where the maintenance duration function is convex and the case where the maintenance duration function is concave, respectively.

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“…Other models consider maintenance scheduling in a flow-shop environment [3], on parallel identical machines [4], a flexible maintenance [5], and a periodic maintenance (see e.g. [6][7][8]). A slightly different paper [9] focuses on scheduling a deteriorating maintenance in flow-shops and open-shops.…”

Section: Introductionmentioning

confidence: 99%

Scheduling a maintenance activity to minimize total weighted completion-time

Mosheiov

Sarig

2009

Computers & Mathematics with Applications

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a b s t r a c tWe study a single machine scheduling problem. The processor needs to go through a maintenance activity, which has to be completed prior to a given deadline. The objective function is minimum total weighted completion time. The problem is proved to be NP-hard, and an introduction of a pseudo-polynomial dynamic programming algorithm indicates that it is NP-hard in the ordinary sense. We also present an efficient heuristic, which is shown numerically to perform well.

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Parallel machine scheduling with almost periodic maintenance and non-preemptive jobs to minimize makespan

Cited by 84 publications

References 10 publications

Task scheduling system for UAV operations in indoor environment

Task scheduling system for UAV operations in indoor environment

Single-machine scheduling with preemptive jobs and workload-dependent maintenance durations

Scheduling a maintenance activity to minimize total weighted completion-time

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