FLOW SHOP使用交叉肠遗传算法进行调度,以最小化PT. XYZ的MAKESPAN

Arnan Jinawi, Budi Santoso, Tutuk Safirin
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引用次数: 0

摘要

大流行时代显然正在迫使社会的每一个要素,特别是工业部门,适应当前的形势。PT. XYZ是其中一个操作流程商店包装行业。如其他行业,这个行业必须限制员工数量,导致生产计划发生一定的变化。为了操作这个过程,这个行业必须提供一个时间表来最小化完工时间。本研究是为了比较工业界使用的LPT方法和CEGA方法。CEGA方法用于对任何作业进行排序,因为它的优先级要按顺序完成。与目前的方法相比,CEGA提供了更好的修复时间,为129,621小时,即15.51%。该方法与先前方法相比,可节省20.13小时或以上,效率达13.44%。在Matlab中运行了CEGA方法,以支持任何优化计算。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PENJADWALAN FLOW SHOP MENGGUNAKAN PENDEKATAN CROSS ENTROPY-GENETIC ALGORITHM UNTUK MEMINIMASI MAKESPAN DI PT. XYZ
ABSTRACT Pandemic era is obviously forcing every elements of society, especially the industrial sectors, to adapt into the current situation. PT. XYZ is one of it that operate the flow shop packaging industry. Such as other industry, this industry had to restrict amount of employees that cause some certain change to the production scheduling. To operate it’s processess, this industry has to provide a schedule to minimize the makespan. This research is done to compare a LPT method used by the industry and CEGA method. CEGA method used to sequence any job due to its priority to be done sequentially. CEGA provide better maksepan that is 129,621 hours or 15,51% different to the current method. This method would save 20,13 hours or more efficeint 13,44% by the method used in prior method. CEGA method is ran with Matlab to support any optimal calculation done.
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