Flexible job shop scheduling is one of the most effective methods for solving multiple varieties and small batch production problems in discrete manufacturing enterprises. However, limitations of actual transportation conditions in the flexible job shop scheduling problem (FJSP) are neglected, which limits its application in actual production. In this paper, the constraint influence imposed by finite transportation conditions in the FJSP is addressed. The coupling relationship between transportation and processing stages is analyzed, and a finite transportation conditions model is established. Then, a three-layer encoding with redundancy and decoding with correction is designed to improve the genetic algorithm and solve the FJSP model. Furthermore, an entity-JavaScript Object Notation (JSON) method is proposed for transmission between scheduling services and Digital Twin (DT) virtual equipment to apply the scheduling results to the DT system. The results confirm that the proposed finite transportation conditions have a significant impact on scheduling under different scales of scheduling problems and transportation times.

灵活的作业车间调度是离散制造企业解决多品种、小批量生产问题最有效的方法之一。然而，柔性作业车间调度问题（FJSP）中忽略了实际运输条件的局限性，这限制了其在实际生产中的应用。在本文中，FJSP 中有限运输条件施加的约束影响得到解决。分析了运输阶段与加工阶段的耦合关系，建立了有限运输条件模型。然后，设计了一个带冗余的三层编码和带校正的解码来改进遗传算法并求解FJSP模型。此外，提出了一种entity-JavaScript Object Notation（JSON）方法用于调度服务和数字孪生（DT）虚拟设备之间的传输，将调度结果应用到DT系统中。结果证实，在不同规模的调度问题和运输时间下，所提出的有限运输条件对调度有显着影响。