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Metaheuristic algorithms for balancing robotic assembly lines with sequence-dependent robot setup times

机译:元启发式算法,用于平衡与顺序相关的机器人设置时间的机器人装配线

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Industries are incorporating robots into assembly lines due to their greater flexibility and reduced costs. Most of the reported studies did not consider scheduling of tasks or the sequence-dependent setup times in an assembly line, which cannot be neglected in a real-world scenario. This paper presents a study on robotic assembly line balancing, with the aim of minimizing cycle time by considering sequence-dependent setup times. A mathematical model for the problem is formulated and CPLEX solver is utilized to solve small-sized problems. A recently developed metaheuristic Migrating Birds Optimization (MBO) algorithm and set of metaheuristics have been implemented to solve the problem. Three different scenarios are tested (with no setup time, and low and high setup times). The comparative experimental study demonstrates that the performance of the MBO algorithm is superior for the tested datasets. The outcomes of this study can help production managers improve their production system in order to perform the assembly tasks with high levels of efficiency and quality.
机译:由于其更大的灵活性和更低的成本,工业界将机器人纳入了装配线。大多数报告的研究都没有考虑装配线上的任务调度或与序列有关的设置时间,这在现实世界中是不能忽略的。本文提出了一项关于机器人装配线平衡的研究,其目的是通过考虑与序列有关的建立时间来最大程度地缩短周期时间。建立了问题的数学模型,并使用CPLEX求解器解决了小型问题。最近开发的元启发式迁徙鸟类优化(MBO)算法和一组元启发式算法已实现以解决该问题。测试了三种不同的方案(无设置时间,低和高设置时间)。对比实验研究表明,MBO算法的性能优于测试数据集。这项研究的结果可以帮助生产经理改善他们的生产系统,以便以高效率和高质量执行装配任务。

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