An improved algorithm to minimize the total completion time in a two-machine no-wait flow-shop with uncertain setup times

IF 1.3 Q4 ENGINEERING, INDUSTRIAL Journal of Project Management Pub Date : 2022-01-01 DOI:10.5267/j.jpm.2021.9.001
Muberra Allahverdi
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引用次数: 5

Abstract

Since scheduling literature has a wide range of uncertainties, it is crucial to take these into account when solving performance measure problems. Otherwise, the performance may severely be affected in a negative way. In this paper, an algorithm is proposed to minimize the total completion time (TCT) of a two-machine no-wait flowshop with uncertain setup times within lower and upper bounds. The results are compared to the best existing algorithm in scheduling literature: the programming language Python is used to generate random samples with respect to various distributions, and the TCT of the proposed algorithm is compared to that of the best existing one. Results reveal that the proposed one significantly outperforms the best one given in literature for all considered distributions. Specifically, the average percentage improvement of the proposed algorithm over the best existing one is over 90%. A test of hypothesis is conducted to further confirm the results.
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具有不确定设置时间的双机无等待流水作业中最小化总完成时间的改进算法
由于调度文献具有广泛的不确定性,因此在解决性能度量问题时考虑这些不确定性是至关重要的。否则,可能会严重影响性能。本文提出了一种使具有不确定设置时间的两机无等待流水车间的总完成时间(TCT)在上界和下界内最小化的算法。将结果与调度文献中现有的最佳算法进行比较:使用编程语言Python对各种分布生成随机样本,并将所提算法的TCT与现有最佳算法的TCT进行比较。结果表明,对于所有考虑的分布,所提出的分布显著优于文献中给出的最佳分布。具体而言,该算法相对于现有最佳算法的平均改进百分比在90%以上。为了进一步证实结果,进行了假设检验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.70
自引率
5.90%
发文量
16
审稿时长
16 weeks
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