Abstract In the practical production scheduling of complex products, the processing time always fails to be accurately estimated as a deterministic value due to the fluctuating manufacturing environment caused by unsteady operating conditions of machines and diverse proficiency levels of workers. Besides, scheduling jobs become restricted by precedence constraints on account of the hierarchical dependencies between manufactured parts defined by Bills-Of-Materials of final products. Hence, this study concentrates on the flexible job shop scheduling problem with job precedence constraints and interval grey processing time (G-FJSP-JPC) under the objective of minimizing the interval grey makespan. The uncertain processing time as well as other time data are represented as interval grey numbers with lower and upper boundaries. Specific operators for dealing with interval grey time numbers are devised to acquire precise grey schedules. A two-vector encoding scheme with job precedence repair mechanism is employed and a heuristic active grey decoding scheme is proposed in which the machine assignment is dynamically determined and the uncertain grey schedule is constructed. A novel multi-micro-swarm leadership hierarchy-based optimization algorithm (M2SLHO) is proposed to tackle G-FJSP-JPC. This algorithm divides search agents into multiple independent micro-swarms in which each one conducts a leadership hierarchy-based search and communicates with others by specific strategies. Extensive computational experiments validate that M2SLHO provides highly promising results for the addressed problem.

中文翻译：

---

具有作业优先约束和间隔灰色处理时间的灵活作业车间调度问题

摘要 在复杂产品的实际生产调度中，由于机器运行条件不稳定和工人熟练程度不同导致制造环境波动，加工时间总是无法准确估计为确定性值。此外，由于最终产品的物料清单定义的制造零件之间的层次结构依赖关系，调度作业受到优先约束的限制。因此，本研究以最小化间隔灰色完工时间为目标，集中研究具有作业优先约束和间隔灰色处理时间（G-FJSP-JPC）的灵活作业车间调度问题。不确定的处理时间以及其他时间数据表示为具有上下边界的区间灰度数。设计用于处理间隔灰色时间数的特定算子以获得精确的灰色时间表。采用具有作业优先级修复机制的二向量编码方案，提出一种动态确定机器分配并构造不确定灰度调度的启发式主动灰度解码方案。提出了一种新的基于多微群领导层级的优化算法（M2SLHO）来解决 G-FJSP-JPC。该算法将搜索代理划分为多个独立的微群，每个微群进行基于领导层级的搜索，并通过特定策略与其他人进行交流。大量的计算实验验证了 M2SLHO 为解决的问题提供了非常有希望的结果。