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    王文艳, 徐震浩, 顾幸生. 离散水波优化算法求解带批处理的混合流水车间批量流调度问题[J]. 华东理工大学学报(自然科学版), 2021, 47(5): 598-608. DOI: 10.14135/j.cnki.1006-3080.20200831001
    引用本文: 王文艳, 徐震浩, 顾幸生. 离散水波优化算法求解带批处理的混合流水车间批量流调度问题[J]. 华东理工大学学报(自然科学版), 2021, 47(5): 598-608. DOI: 10.14135/j.cnki.1006-3080.20200831001
    WANG Wenyan, XU Zhenhao, GU Xingsheng. Discrete Water Wave Optimization Algorithm for Hybrid Flowshop Lot-Streaming Scheduling Problem with Batch Processing[J]. Journal of East China University of Science and Technology, 2021, 47(5): 598-608. DOI: 10.14135/j.cnki.1006-3080.20200831001
    Citation: WANG Wenyan, XU Zhenhao, GU Xingsheng. Discrete Water Wave Optimization Algorithm for Hybrid Flowshop Lot-Streaming Scheduling Problem with Batch Processing[J]. Journal of East China University of Science and Technology, 2021, 47(5): 598-608. DOI: 10.14135/j.cnki.1006-3080.20200831001

    离散水波优化算法求解带批处理的混合流水车间批量流调度问题

    Discrete Water Wave Optimization Algorithm for Hybrid Flowshop Lot-Streaming Scheduling Problem with Batch Processing

    • 摘要: 针对实际生产系统中生产方式复杂多样的特点,研究了带批处理的混合流水车间批量流调度问题。综合考虑批处理机容量和不相关离散机加工能力,提出了一种可变分批方法,以最小化完工时间为目标建立了调度模型,并提出了一种动态连续加工策略来优化目标函数。同时提出了一种离散水波优化(DWWO)算法求解模型。结合分批特点与优化目标,设计了4种解码方式对机器选择及工件的加工顺序进行优化;利用块最优插入、交叉操作和多邻域搜索对操作算子进行改进,增强了局部搜索能力;提出了一种替换差解的操作来提高算法的收敛能力。最后,采用实验设计的方法对算法的参数进行了标定;并设计了不同规模的算例,对算法的性能进行评估。实验结果表明DWWO算法能够有效解决带批处理的混合流水车间批量流调度问题。

       

      Abstract: Aiming at the complexity and variety of production modes in the actual production system, this paper investigates the hybrid flowshop lot-streaming scheduling problem with batch processing. A variable batching method is proposed by considering the capacity of batch machine and the processing ability of unrelated machines. A scheduling model is established to minimize the completion time via dynamic continuous processing strategy. At the same time, a discrete water wave optimization (DWWO) is proposed to solve the scheduling model. According to the characteristic of batching and optimization objectives, four decoding methods are designed to optimize the machine selection and processing sequence of jobs. By the block optimal insertion, cross operation, and multi neighborhood search, the operation operators are improved for enhancing the local search ability. Moreover, an operation of replacing inferior solution is proposed to improve the convergence ability of the proposed algorithm. Finally, the experimental design method is used to calibrate the parameters of DWWO, and different scale examples are designed to evaluate the performance of DWWO. It is shown via the experimental results that the proposed DWWO algorithm can effectively deal with the hybrid flowshop lot-streaming scheduling problem with batch processing.

       

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