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Disruption Management for Predictable New Job Arrivals in Cloud Manufacturing

机译:云制造业可预测新工作的中断管理

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摘要

Manufacturing resources are shared and centrally managed on the cloud platform in cloud manufacturing, which is a new model of modern manufacturing. The production data are collected, which can be used to predict the manufacturing events. Based on those, disruption problems of scheduling should be researched from a new point of view. In this paper, new job arrivals were considered as the disruption event. The time of the occurrence of disruption was predictable in contrast to uncertainty. Alternative subcontractors chosen from the cloud platform were available for outsourcing with different processing prices and transporting distances. The objective of the original scheduling, the deviation between the new schedule and the old one, and the outsourcing cost were all considered. To express the problem, mathematical models and a three-field notation model were constructed. To solve the problem, a hybrid quantum-inspired chaotic group leader optimization algorithm was proposed, in which a hybrid encoding way was applied. To verify the algorithm, experiments were carried out. The results showed that the proposed algorithm performs well.
机译:制造资源是共享的,并在云制造业的云平台上集中管理,这是现代制造业的新模式。收集生产数据,可用于预测制造事件。基于这些,应从新的角度来研究调度的中断问题。在本文中,新的就业人士被视为中断事件。与不确定性相比,发生破坏的时间是可预测的。从云平台中选择的替代分包商可用于外包,以不同的加工价格和运输距离。原始调度的目的,新时间表与旧的偏差以及外包成本都得到了考虑。为了表达问题,构建了数学模型和三场符号符号模型。为了解决问题,提出了一种混合量子启发混沌组领导算法,其中应用了混合编码方式。为了验证算法,进行实验。结果表明,所提出的算法表现良好。

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