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首页> 外文期刊>International Journal of Production Research >An immune algorithm for scheduling a hybrid flow shop with sequence-dependent setup times and machines with random breakdowns
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An immune algorithm for scheduling a hybrid flow shop with sequence-dependent setup times and machines with random breakdowns

机译：一种免疫算法，用于调度具有顺序依赖的建立时间和具有随机故障的机器的混合流水车间

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摘要

Much of the research on operations scheduling problems has either ignored setup times or assumed that setup times on each machine are independent of the job sequence. Furthermore, most scheduling problems that have been discussed in the literature are under the assumption that machines are continuously available. Nevertheless, in most real-life industries a machine can be unavailable for many reasons, such as unanticipated breakdowns (stochastic unavailability), or due to scheduled preventive maintenance where the periods of unavailability are known in advance (deterministic unavailability). This paper deals with hybrid flow shop scheduling problems in which there are sequence-dependent setup times (SDSTs), and machines suffer stochastic breakdowns, to optimise objectives based on the expected makespan. With the increase in manufacturing complexity, conventional scheduling techniques for generating a reasonable manufacturing schedule have become ineffective. An immune algorithm (IA) can be used to tackle complex problems and produce a reasonable manufacturing schedule within an acceptable time. In this research, a computational method based on a clonal selection principle and an affinity maturation mechanism of the immune response is used. This paper describes how we can incorporate simulation into an immune algorithm for the scheduling of a SDST hybrid flow shop with machines that suffer stochastic breakdowns. The results obtained are analysed using a Taguchi experimental design.
机译：有关操作调度问题的许多研究都忽略了设置时间，或者假设每台机器上的设置时间与作业顺序无关。此外，文献中已讨论的大多数调度问题都是在假设机器可以连续使用的前提下进行的。但是，在大多数现实生活中，机器可能由于多种原因而无法使用，例如意外故障（随机性不可用），或者由于事先计划了不可用时间（确定性不可用）而进行的定期预防性维护。本文讨论了混合流水车间调度问题，其中存在依赖于序列的建立时间（SDST），并且机器遭受随机故障的影响，从而根据预期的工期优化目标。随着制造复杂性的增加，用于生成合理制造计划的常规计划技术变得无效。免疫算法（IA）可用于解决复杂问题并在可接受的时间内制定合理的生产计划。在这项研究中，使用了一种基于克隆选择原理和免疫应答亲和力成熟机制的计算方法。本文介绍了如何将仿真合并到免疫算法中，以调度具有随机故障的机器的SDST混合流水车间。使用田口实验设计分析获得的结果。

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