Single-machine scheduling with past-sequence-dependent setup times and learning effects: a parametric analysis

doi:10.1080/00207721003718436

淡江大學機構典藏 > 工學院 > 資訊工程學系暨研究所 > 期刊論文 > Item 987654321/121407

Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/121407

Title:	Single-machine scheduling with past-sequence-dependent setup times and learning effects: a parametric analysis
Authors:	Mani, V.;Chang, P. C.;Chen, S. H.
Keywords:	scheduling;setup times;learning effect
Date:	2011-12
Issue Date:	2021-09-30 12:10:28 (UTC+8)
Abstract:	In this article, we consider the single-machine scheduling problem with past-sequence-dependent (p-s-d) setup times and a learning effect. The setup times are proportional to the length of jobs that are already scheduled; i.e. p-s-d setup times. The learning effect reduces the actual processing time of a job because the workers are involved in doing the same job or activity repeatedly. Hence, the processing time of a job depends on its position in the sequence. In this study, we consider the total absolute difference in completion times (TADC) as the objective function. This problem is denoted as 1/LE, s psd /TADC in Kuo and Yang (2007) (‘Single Machine Scheduling with Past-sequence-dependent Setup Times and Learning Effects’, Information Processing Letters, 102, 22–26). There are two parameters a and b denoting constant learning index and normalising index, respectively. A parametric analysis of b on the 1/LE, s psd /TADC problem for a given value of a is applied in this study. In addition, a computational algorithm is also developed to obtain the number of optimal sequences and the range of b in which each of the sequences is optimal, for a given value of a. We derive two bounds b* for the normalising constant b and a* for the learning index a. We also show that, when a < a* or b > b*, the optimal sequence is obtained by arranging the longest job in the first position and the rest of the jobs in short processing time order.
Relation:	International Journal of Systems Science 42(12), p.2097–2102
DOI:	10.1080/00207721003718436
Appears in Collections:	[資訊工程學系暨研究所] 期刊論文

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