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A Study of Distributed Scheduling Problem with Machine Maintenance

机译:机器维护分布式调度问题研究

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In this paper, we study the influence of machine maintenance to distributed scheduling problems. Distributed scheduling is aiming to maximize the system efficiency by simultaneously solving two problems: (i) allocation of jobs to suitable factories, and (ii) determination of the corresponding production scheduling in each factory. Scheduling of machine maintenance problems aim to reduce the effect of breakdown and maximize the facility availability at minimum cost. However, in many distributed scheduling problems, machine scheduling assumes that machines are available all the time. In fact, every machine requires maintenance, and the maintenance policy directly affects the machine's availability. Consequently, it interrupts the production scheduling determined. This paper designed a hypothetical distributed scheduling model with three different problem sizes to demonstrate the significance of simultaneously solving machine maintenance problem with distributed scheduling problem. We applied Genetic Algorithm with Dominant Genes methodology to solve the model. Several optimization approaches, including separating and integrating the two problems, are tested and compared. The results show the merit of integration.
机译:本文研究了机器维护对分布式调度问题的影响。分布式调度旨在通过同时解决两个问题来最大限度地提高系统效率:(i)将作业分配给合适的工厂,(ii)确定每个工厂的相应生产调度。机器维护问题的调度旨在降低故障的效果,最大限度地提高设施可用性。但是,在许多分布式调度问题中,机器调度假定机器是一直上可用的。实际上,每台机器都需要维护,维护策略直接影响机器的可用性。因此,它中断确定的生产调度。本文设计了一个假设的分布式调度模型,具有三种不同的问题尺寸,以展示与分布式调度问题同时解决机器维护问题的重要性。我们用显性基因方法应用了遗传算法来解决模型。测试和比较了几种优化方法,包括分离和整合两个问题。结果表明了整合的优点。

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