带附加约束的柔性作业车间调度问题的多目标超启发式算法

2016 3rd International Conference on Soft Computing & Machine Intelligence (ISCMI) Pub Date : 2016-11-01 DOI:10.1109/ISCMI.2016.46

J. Grobler

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引用次数: 4

摘要

本文提出了一种多目标超启发式(MOO-HMHH)算法，用于求解具有序列依赖性的柔性作业车间调度问题(FJSP)。在实际客户数据集上对算法的两种变体进行了实现和评估。超启发式算法与其组成算法进行了很好的比较，并且在提高超启发式的通用性方面获得了有希望的结果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A Multi-objective Hyper-Heuristic for the Flexible Job Shop Scheduling Problem with Additional Constraints

This paper proposes a multi-objective hyperheuristic (MOO-HMHH) algorithm for the flexible job shop scheduling problem (FJSP) with sequence-dependent set-up times, auxiliary resources and machine down time. Two variations of the algorithm were implemented and evaluated on real customer datasets. The hyper-heuristic algorithms compared well to their constituent algorithms and promising results were obtained with respect to the increased generality of the hyperheuristics.

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2016 3rd International Conference on Soft Computing & Machine Intelligence (ISCMI)

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