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Rough mill component scheduling: heuristic search versus genetic algorithms

机译:粗磨机组件调度:启发式搜索与遗传算法

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Rough mill production systems cut lumber into smaller components needed to produce wood products. Because of the system's limited sorting capacity, rough mill operators need to schedule when different component sizes are made, a process called part scheduling and replacement. This scheduling process is significant because it greatly affects system performance. Three component scheduling algorithms are examined in this paper: a heuristic method that mimics how human operators manually schedule components; and two methods based on genetic algorithms, the simple genetic algorithm and the ordering messy genetic algorithm. The performance of the algorithms is analyzed and tested on four cutting bills. Results show that the ordering messy genetic algorithm outperformed the simple genetic algorithm, and heuristic component replacement performed better than replacement based on the genetic algorithm's objective function. Also, heuristic cut-list selection performed better on cutting bills with more short pieces, whereas GA cut-list selection performed better on bills it with longer pieces.
机译:粗磨机生产系统将木材切成生产木制品所需的较小部件。由于系统的排序能力有限,粗磨磨机运算符需要调度不同的组件大小,称为零件调度和更换的过程。此调度过程很大,因为它会极大地影响系统性能。本文审查了三个组件调度算法:一种启发式方法,模仿人类运营商如何手动调度组件;基于遗传算法的两种方法,简单的遗传算法和排序凌乱遗传算法。分析算法的性能并在四个切割纸币上进行测试。结果表明,订购杂乱遗传算法优于简单的遗传算法,并且启发式组件更换比基于遗传算法的目标函数更好。此外,启发式裁员选择在切割纸屑上更好地执行,而GA Cut-List选择在较长的碎片上表现更好。

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