Study on Due-Date Assignment Scheduling with Setup Times and General Truncated Learning Effects

Yifu Feng, Zonghai Hu (), Rui Si () and Ji-Bo Wang ()
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Yifu Feng: Anqing Medical College, Anhui, Anqing, P. R. China
Zonghai Hu: Anqing Medical College, Anhui, Anqing, P. R. China
Rui Si: Anqing Medical College, Anhui, Anqing, P. R. China
Ji-Bo Wang: School of Science, Shenyang Aerospace University, Shenyang, P. R. China

Asia-Pacific Journal of Operational Research (APJOR), 2024, vol. 41, issue 01, 1-16

Abstract: This paper concentrates on the single-machine scheduling problem with past-sequence-dependent setup times and general truncated learning effects, where the job processing times are non-increasing function of their positions in a sequence. Under common, slack and different (unrestricted) due-date assignments, our goal is to minimize the weighted sum of number of early/tardy jobs and due-date assignment cost, where the weight is not related to the job but to a position, i.e., the position-dependent weight. Under the three due-date assignments, some optimal properties and three optimal solution algorithms are proposed to solve these problems, respectively.

Keywords: Scheduling; due-date assignment; position-dependent weights; setup times; learning effect (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1142/S0217595923500069

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