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An adaptive neuro fuzzy inference system for makespan estimation in multiprocessor no-wait two stage flow shop

机译:自适应神经模糊推理系统,用于多处理器无等待两阶段流水线的工期估计

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摘要

In a flow shop scheduling problem, no-wait processing is becoming an important subject where the subsequent operations are performed with no-waiting time in between. In addition, it is important to estimate the schedule performance in terms of given criteria. This enables managers to conduct a reliable logistic planning while estimating robust job completion times. In this study, six heuristic algorithms are used to solve a no-wait two stage flexible flow shop with minimising makespan. Furthermore, an adaptive neuro fuzzy inference system (ANFIS) with neural network and fuzzy theory is applied for estimating the makespan. The robustness of the proposed ANFIS using the six heuristic scheduling algorithms is testified by comparing its performance with that of the actual schedule performance. This is followed by concluding remarks and potential area for further researches.
机译:在流水车间调度问题中,无等待处理正在成为重要的主题,在该过程中,随后的操作以其间没有等待时间进行。另外,重要的是要根据给定的标准来评估进度表的性能。这使管理人员能够进行可靠的物流计划,同时估计可靠的工作完成时间。在这项研究中,使用六种启发式算法来解决无等待的两阶段灵活流水车间,并最大程度地缩短了制造时间。此外,将具有神经网络和模糊理论的自适应神经模糊推理系统(ANFIS)用于估计制造期限。通过将其性能与实际调度性能进行比较,证明了使用六种启发式调度算法的拟议ANFIS的鲁棒性。接下来是结语和有待进一步研究的潜在领域。

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