In the mixed-model assembly line balancing and sequencing problem (MALBSP), workstations are assumed to be constantly available. The failure of any workstation will make the entire assembly line stop working. Preventive maintenance (PM) is a way to maintain the workstation before its failure, reduce unexpected downtime, and prolong its useful life. Previous studies have considered PM scenarios (PMS) in the simple and U-shaped assembly line to improve production efficiency and smoothness effectively, but not in the mixed-model assembly line. This paper fills this research gap, and the MALBSP considering PMS (MALBSP_PMS) is studied in this paper. A mixed-integer linear programming model is proposed to minimize makespan and task alteration. A migrating birds optimization algorithm is improved (IMBO) to obtain well-distributed Pareto frontier solutions. This algorithm designs a restart mechanism and an intra-population crossover operator to avoid falling into the local optimal and enhance its searchability. Experimental results demonstrate the effectiveness of two improvements and the IMBO algorithm. In addition, a real-world case study is introduced to illustrate the importance of considering PM scenarios in MALBSP.

在混合模型装配线平衡和排序问题 (MALBSP) 中，假定工作站始终可用。任何一个工作站出现故障都会使整条流水线停止工作。预防性维护 (PM) 是一种在工作站出现故障之前对其进行维护、减少意外停机时间并延长其使用寿命的方法。以往的研究考虑了简单和 U 型装配线中的 PM 场景 (PMS) 以有效提高生产效率和平稳性，但在混合模型装配线中没有考虑。本文填补了这一研究空白，本文研究了考虑PMS的MALBSP（MALBSP_PMS）。提出了一种混合整数线性规划模型，以最大限度地减少完工时间和任务变更。改进了候鸟优化算法（IMBO）以获得分布良好的帕累托前沿解。该算法设计了重启机制和种群内交叉算子，避免陷入局部最优，增强了算法的可搜索性。实验结果证明了两种改进和IMBO算法的有效性。此外，还介绍了一个真实案例研究，以说明在 MALBSP 中考虑 PM 场景的重要性。