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首页> 外文期刊>International Journal of Production Research >A hybrid artificial bee colony algorithm for a flexible job shop scheduling problem with overlapping in operations
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A hybrid artificial bee colony algorithm for a flexible job shop scheduling problem with overlapping in operations

机译：具有重叠操作的柔性作业车间调度问题的混合人工蜂群算法

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摘要

Overlapping in operations is an effective technology for productivity improvement in modern manufacturing systems. Thus far, however, there are still rare works on flexible job shop scheduling problems (FJSPs) concerning this strategy. In this paper, we present a hybrid artificial bee colony (hyABC) algorithm to minimise the total flowtime for a FJSP with overlapping in operations. In the proposed hyABC, a dynamic scheme is introduced to fine-tune the search scope adaptively. In view of poor exploitation ability of artificial bee colony algorithm, a modified migrating birds optimisation algorithm (MMBO) is developed and integrated into the search process for better balancing global exploration and local exploitation. In MMBO, a forward share strategy with one-job based crossover is designed to make good use of valuable information from behind solutions. Besides, an improved downward share scheme is adopted to increase diversification of the population, and thus alleviate the premature convergence. Extensive experiments based on benchmark instances with different scales are carried out and comparisons with other recent algorithms identify the effectiveness of the proposed hyABC.
机译：重叠操作是提高现代制造系统生产率的有效技术。但是，到目前为止，关于此策略的灵活的作业车间调度问题（FJSP）仍然很少见。在本文中，我们提出了一种混合人工蜂群（hyABC）算法，以最小化操作重叠的FJSP的总流动时间。在提出的hyABC中，引入了一种动态方案来自适应地微调搜索范围。针对人工蜂群算法开发能力差的问题，提出了一种改进的迁徙鸟类优化算法（MMBO）并将其集成到搜索过程中，以更好地平衡全球勘探与局部开发。在MMBO中，设计了一种基于单工交叉的前瞻性共享策略，以充分利用来自背后解决方案的宝贵信息。此外，还采用了改进的向下分配方案，以增加人口的多样化，从而减轻过早的趋同。基于具有不同规模的基准实例进行了广泛的实验，并与其他最新算法进行了比较，从而确定了所提出的hyABC的有效性。

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