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A fast and effective heuristic for smoothing workloads on assembly lines: algorithm design and experimental analysis

机译:一种快速有效的启发式方法,可简化装配线上的工作量:算法设计和实验分析

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Workload smoothing on assembly lines, which aims to evenly assign tasks to stations, supports workforce planning and resource optimization. In this paper, we study smoothing assembly lines and develop a problem-specific heuristic to efficiently solve large-sized instances. To build solutions, the algorithm uses a number of well-known priority rules for task assignment in conjunction with a probabilistic decision-making procedure for closing workstations. We conduct an experimental design for selecting the best performing priority rules and for tuning the probabilistic decision-making procedure. The efficiency of our algorithm is tested and demonstrated through an extensive experimental study. (C) 2019 Elsevier Ltd. All rights reserved.
机译:旨在将任务均匀分配给工作站的装配线上的工作负载平滑,支持劳动力规划和资源优化。在本文中,我们研究了平滑装配线并开发了特定于问题的启发式方法来有效地解决大型实例。为了构建解决方案,该算法将许多众所周知的优先级规则用于任务分配,并结合用于关闭工作站的概率决策程序。我们进行实验设计,以选择性能最佳的优先级规则并调整概率决策程序。通过广泛的实验研究测试并证明了我们算法的效率。 (C)2019 Elsevier Ltd.保留所有权利。

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