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The assembly line balancing and scheduling problem with sequence-dependent setup times: problem extension, model formulation and efficient heuristics

机译:具有与序列有关的建立时间的装配线平衡和调度问题:问题扩展,模型制定和高效的启发式

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Assembly line balancing problems (ALBP) consist of distributing the total workload for manufacturing any unit of the products to be assembled among the work stations along a manufacturing line as used in the automotive or the electronics industries. Usually, theory assumes that, within each station, tasks can be executed in an arbitrary precedence-feasible sequence without changing station times. In practice, however, the task sequence may influence the station time considerably as sequence-dependent setups (e.g., walking distances, tool changes) have to be considered. Including this aspect leads to a joint balancing and scheduling problem, which we call SUALBSP (setup assembly line balancing and scheduling problem). In this paper, we modify the problem by modeling setups more realistically, give a new, more compact mathematical model formulation and develop effective heuristic solution procedures. Computational experiments based on existing and new data sets indicate that the new procedures outperform formerly proposed heuristics. They are able to solve problem instances of real-world size with small deviations from optimality in computation times short enough to be accepted in real-world decision support systems.
机译:装配线平衡问题(ALBP)包括沿着汽车或电子行业中使用的生产线在工作站之间分配用于制造要组装的任何产品单元的总工作量。通常,理论假设,在每个工作站中,可以按照任意优先级可行的顺序执行任务,而无需更改工作站时间。然而,实际上,由于必须考虑与序列有关的设置(例如,步行距离,工具更换),任务序列可能会极大地影响工位时间。包括此方面会导致联合的平衡和调度问题,我们称其为SUALBSP(设置装配线平衡和调度问题)。在本文中,我们通过更现实地建模来修正问题,给出新的,更紧凑的数学模型公式并开发有效的启发式求解程序。基于现有数据集和新数据集的计算实验表明,新程序的性能优于先前提出的启发式算法。他们能够解决实际大小的问题实例,并且在计算时间上与最优性之间的偏差很小,不足以被现实决策支持系统接受。

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