This article proposes a novel biogeography-based optimization (NBBO) algorithm to solve the distributed assembly permutation flow-shop scheduling problem with sequence-dependent set-up times (DAPFSP-SDST). The optimization objective of this problem is minimizing the maximum completion time (makespan). In the initialization phase, NBBO generates two kinds of feasible solutions. Secondly, the linear migration model is replaced with the sinusoidal migration model and a modified product insertion method is performed in the migration phase. Then, in the mutation phase, a job insertion method is used to adjust the processing order of jobs in each product. A local search method based on SDST is combined to jump out of local optima. Finally, simulation experiments based on 540 test instances and comparisons with seven existing algorithms as well as one simple biogeography-based optimization algorithm verify the superiority of NBBO.

本文提出了一种新的基于生物地理学的优化（NBBO）算法来解决具有序列相关设置时间的分布式装配置换流水车间调度问题（DAPFSP-SDST）。这个问题的优化目标是最小化最大完成时间（makespan）。在初始化阶段，NBBO 生成两种可行解。其次，将线性偏移模型替换为正弦偏移模型，并在偏移阶段执行改进的乘积插入方法。然后，在变异阶段，使用作业插入的方法来调整每个产品中作业的处理顺序。结合基于SDST的局部搜索方法跳出局部最优。最后，