The Dynamic Flow Shop Scheduling Problem with JIT Philosophy and Common Due Date

Most studies on common due date problems discuss the topic in the context of solving the minimum penalty value for the single-machine or parallel machine scheduling environment. This study extends the problem of the common due date to the dynamic flow shop environment and proposes the enhanced heuri...

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Published inMathematical problems in engineering Vol. 2022; pp. 1 - 12
Main Authors Huang, Wen-Tso, Chen, Ping-Shun, Chen, Gary Yu-Hsin, Dang, Jr-Fong
Format Journal Article
LanguageEnglish
Published New York Hindawi 07.02.2022
John Wiley & Sons, Inc
Subjects
Algorithms
Assignment problem
Case studies
Costs
Dynamic programming
Efficiency
Employment
Evolution & development
Fines & penalties
Genetic algorithms
Genomes
Heuristic methods
Integer programming
Job shop scheduling
Job shops
Literature reviews
Manufacturing
Monte Carlo simulation
Mutation
Scheduling
Online AccessGet full text
ISSN1024-123X
1026-7077
1563-5147
1563-5147
DOI10.1155/2022/9970988

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Abstract Most studies on common due date problems discuss the topic in the context of solving the minimum penalty value for the single-machine or parallel machine scheduling environment. This study extends the problem of the common due date to the dynamic flow shop environment and proposes the enhanced heuristic algorithm to solve the minimum penalty value. The enhanced heuristic algorithm is characterized by designating mutant genomes of the child as the genomes located at the central location before mutation. The advantage is to integrate the successful experiences of the conventional common due date algorithm to improve the efficiency of the proposed heuristic algorithm. The performance of both algorithms is analyzed in terms of uniformly distributed job numbers, processing time, early penalty, and late penalty. The resulting outcomes indicate that the enhanced heuristic algorithm outperforms the conventional CDDA and EDD proposed by previous studies in the average penalties.
AbstractList Most studies on common due date problems discuss the topic in the context of solving the minimum penalty value for the single-machine or parallel machine scheduling environment. This study extends the problem of the common due date to the dynamic flow shop environment and proposes the enhanced heuristic algorithm to solve the minimum penalty value. The enhanced heuristic algorithm is characterized by designating mutant genomes of the child as the genomes located at the central location before mutation. The advantage is to integrate the successful experiences of the conventional common due date algorithm to improve the efficiency of the proposed heuristic algorithm. The performance of both algorithms is analyzed in terms of uniformly distributed job numbers, processing time, early penalty, and late penalty. The resulting outcomes indicate that the enhanced heuristic algorithm outperforms the conventional CDDA and EDD proposed by previous studies in the average penalties.
Author Huang, Wen-Tso
Chen, Gary Yu-Hsin
Dang, Jr-Fong
Chen, Ping-Shun
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Copyright Copyright © 2022 Wen-Tso Huang et al.
Copyright © 2022 Wen-Tso Huang et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0
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SubjectTerms Algorithms
Assignment problem
Case studies
Costs
Dynamic programming
Efficiency
Employment
Evolution & development
Fines & penalties
Genetic algorithms
Genomes
Heuristic methods
Integer programming
Job shop scheduling
Job shops
Literature reviews
Manufacturing
Monte Carlo simulation
Mutation
Scheduling
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Title The Dynamic Flow Shop Scheduling Problem with JIT Philosophy and Common Due Date
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