There are various uncertain disturbances in the actual manufacturing environment, which makes dynamic multiobjective flexible scheduling problem of flexible job shop (MDFJSP) become the research focus in the field of optimal scheduling. In this paper, MDFJSP in the environment of temporary order insertion uncertainty is studied, and a multiobjective dynamic scheduling scheme based on rescheduling index and adaptive nondominated sorting genetic algorithm (NSGA-II) is proposed. First, based on the actual manufacturing environment, the mathematical model of the traditional flexible job shop scheduling problem is improved, and the multiobjective dynamic rescheduling model of flexible work center is established. Then, the existing rescheduling mechanisms are summarized, and a rescheduling hybrid driving mechanism based on the rescheduling index is proposed to enable it to reschedule and drive according to the actual situation. Finally, the shortcomings of the traditional multiobjective scheduling algorithm NSGA-II are analyzed, the adaptive cross mutation strategy and the simplified harmonic normalized distance measure method are proposed to improve it, and an adaptive multiobjective dynamic scheduling algorithm NSGA-II (MDSA-NSGA-II) is formed. To analyze the performance of this algorithm, the performance of this algorithm is compared with five classical flexible job shop multiobjective scheduling algorithms in international general examples, and the effectiveness is verified by real aircraft production examples. The experimental results fully show that MDSA-NSGA-II has good performance in solving MDFJSP.

中文翻译：

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一种求解动态多目标柔性调度问题的自适应多目标进化算法

实际制造环境中存在各种不确定性扰动，这使得柔性作业车间动态多目标柔性调度问题(MDFJSP)成为优化调度领域的研究热点。本文针对临时插单不确定环境下的MDFJSP进行研究，提出了一种基于重调度指标和自适应非支配排序遗传算法（NSGA-II）的多目标动态调度方案。首先，基于实际制造环境，改进传统柔性作业车间调度问题的数学模型，建立柔性工作中心的多目标动态再调度模型。然后，总结了现有的重新调度机制，并提出了一种基于重调度指标的重调度混合动力驱动机制，使其能够根据实际情况进行重调度和驱动。最后，分析了传统多目标调度算法NSGA-II的不足，提出了自适应交叉变异策略和简化调和归一化距离度量方法对其进行改进，提出了一种自适应多目标动态调度算法NSGA-II（MDSA-NSGA- II)形成。为了分析该算法的性能，将其与5种经典的柔性作业车间多目标调度算法在国际通用实例中进行了性能比较，并通过实机生产实例验证了其有效性。实验结果充分表明MDSA-NSGA-II在求解MDFJSP方面具有良好的性能。