Abstract: Aiming at the problem that the sequencing performance which would be executed on a mixed model assembly line might deteriorate or become infeasible due to material unkitting,a multi-objective resequencing model of mixed model assembly line based on minimum sequencing deviation was proposed to guarantee the stability of production process when the initial sequencing transitioned to resequencing,and a Non-dominated Sorting Genetic Algorithm (NSGA-II) was designed to solve this model.To avoid the problems such as overcapacity in current production cycle and poor capacity in next production cycle,a bicycle joint optimization strategy and a decomposition method based on production capacity of assembly line for mixed model assembly line resequencing were presented.For the case of a mixed model assembly line in an air conditioner manufacturing company,the proposed method was used to solve the resequencing caused by material unkitting,and the non-dominated Pareto solution set with small sequencing deviation and well performance was obtained.Compared with the existing heuristic resequencing results of the case company,the results showed that the proposed method could effectively solve the influence of material unkitting on performance of mixed model assembly line.

Key words: mixed model assembly line, resequencing, genetic algorithms, multi-objective optimization

摘要： 针对混流装配线由于物料不齐套导致将要执行的生产排序性能恶化或不可行的问题,为保证从初始排序过渡到重排序时生产准备过程的稳定性,提出基于最小化排序偏差指标的混流装配线重排序模型。采用非支配遗传算法进行求解,为避免当前周期的能力剩余和下一周期能力不足等问题,保证生产线的整体排序性能和充分利用当前周期的装配能力,采用两周期联合优化策略和基于装配能力的分解策略。针对某空调混流装配线实例,采用所提方法求解物料不齐套引起的重排序,得到性能良好的非支配Pareto解集,并与企业现有的启发式规则的重排序结果进行比较,表明所提方法能够有效解决物料不齐套对装配线排序性能的影响。

关键词: 混流装配线, 重排序, 遗传算法, 多目标优化