A bi-criterion sequence-dependent scheduling problem with order deliveries
The manufacturing sector faces unprecedented challenges, including intense competition, a surge in product varieties, heightened customization demands, and shorter product life cycles. These challenges underscore the critical need to optimize manufacturing systems. Among the most enduring and comple...
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| Format: | Article |
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PeerJ Inc.
2024-01-01
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| Series: | PeerJ Computer Science |
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| Online Access: | https://peerj.com/articles/cs-1763.pdf |
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| author | Jian-You Xu Win-Chin Lin Kai-Xiang Hu Yu-Wei Chang Wen-Hsiang Wu Peng-Hsiang Hsu Tsung-Hsien Wu Chin-Chia Wu |
| author_facet | Jian-You Xu Win-Chin Lin Kai-Xiang Hu Yu-Wei Chang Wen-Hsiang Wu Peng-Hsiang Hsu Tsung-Hsien Wu Chin-Chia Wu |
| author_sort | Jian-You Xu |
| collection | DOAJ |
| description | The manufacturing sector faces unprecedented challenges, including intense competition, a surge in product varieties, heightened customization demands, and shorter product life cycles. These challenges underscore the critical need to optimize manufacturing systems. Among the most enduring and complex challenges within this domain is production scheduling. In practical scenarios, setup time is whenever a machine transitions from processing one product to another. Job scheduling with setup times or associated costs has garnered significant attention in both manufacturing and service environments, prompting extensive research efforts. While previous studies on customer order scheduling primarily focused on orders or jobs to be processed across multiple machines, they often overlooked the crucial factor of setup time. This study addresses a sequence-dependent bi-criterion scheduling problem, incorporating order delivery considerations. The primary objective is to minimize the linear combination of the makespan and the sum of weighted completion times of each order. To tackle this intricate challenge, we propose pertinent dominance rules and a lower bound, which are integral components of a branch-and-bound methodology employed to obtain an exact solution. Additionally, we introduce a heuristic approach tailored to the problem’s unique characteristics, along with three refined variants designed to yield high-quality approximate solutions. Subsequently, these three refined approaches serve as seeds to generate three distinct populations or chromosomes, each independently employed in a genetic algorithm to yield a robust approximate solution. Ultimately, we meticulously assess the efficacy of each proposed algorithm through comprehensive simulation trials. |
| first_indexed | 2024-03-08T16:37:23Z |
| format | Article |
| id | doaj.art-982ef34374264218a852dc5af6e3be62 |
| institution | Directory Open Access Journal |
| issn | 2376-5992 |
| language | English |
| last_indexed | 2024-03-08T16:37:23Z |
| publishDate | 2024-01-01 |
| publisher | PeerJ Inc. |
| record_format | Article |
| series | PeerJ Computer Science |
| spelling | doaj.art-982ef34374264218a852dc5af6e3be622024-01-05T15:05:26ZengPeerJ Inc.PeerJ Computer Science2376-59922024-01-0110e176310.7717/peerj-cs.1763A bi-criterion sequence-dependent scheduling problem with order deliveriesJian-You Xu0Win-Chin Lin1Kai-Xiang Hu2Yu-Wei Chang3Wen-Hsiang Wu4Peng-Hsiang Hsu5Tsung-Hsien Wu6Chin-Chia Wu7College of Information Science and Engineering, Northeastern University, Shenyang, ChinaDepartment of Statistics, Feng Chia University, Taichung, TaiwanDepartment of Statistics, Feng Chia University, Taichung, TaiwanDepartment of Statistics, Feng Chia University, Taichung, TaiwanDepartment of Healthcare Management, Yuanpei University of Medical Technology, Hsinchu, TaiwanDepartment of Business Admistration, University of Kang-Ning, Taipei, TaiwanBachelor’s Program in Business Management, Fu Jen Catholic University, New Taipei City, TaiwanDepartment of Statistics, Feng Chia University, Taichung, TaiwanThe manufacturing sector faces unprecedented challenges, including intense competition, a surge in product varieties, heightened customization demands, and shorter product life cycles. These challenges underscore the critical need to optimize manufacturing systems. Among the most enduring and complex challenges within this domain is production scheduling. In practical scenarios, setup time is whenever a machine transitions from processing one product to another. Job scheduling with setup times or associated costs has garnered significant attention in both manufacturing and service environments, prompting extensive research efforts. While previous studies on customer order scheduling primarily focused on orders or jobs to be processed across multiple machines, they often overlooked the crucial factor of setup time. This study addresses a sequence-dependent bi-criterion scheduling problem, incorporating order delivery considerations. The primary objective is to minimize the linear combination of the makespan and the sum of weighted completion times of each order. To tackle this intricate challenge, we propose pertinent dominance rules and a lower bound, which are integral components of a branch-and-bound methodology employed to obtain an exact solution. Additionally, we introduce a heuristic approach tailored to the problem’s unique characteristics, along with three refined variants designed to yield high-quality approximate solutions. Subsequently, these three refined approaches serve as seeds to generate three distinct populations or chromosomes, each independently employed in a genetic algorithm to yield a robust approximate solution. Ultimately, we meticulously assess the efficacy of each proposed algorithm through comprehensive simulation trials.https://peerj.com/articles/cs-1763.pdfSchedulingSequence-dependentBranch-and-boundGenetic algorithmSetup timeCustomer order scheduling |
| spellingShingle | Jian-You Xu Win-Chin Lin Kai-Xiang Hu Yu-Wei Chang Wen-Hsiang Wu Peng-Hsiang Hsu Tsung-Hsien Wu Chin-Chia Wu A bi-criterion sequence-dependent scheduling problem with order deliveries PeerJ Computer Science Scheduling Sequence-dependent Branch-and-bound Genetic algorithm Setup time Customer order scheduling |
| title | A bi-criterion sequence-dependent scheduling problem with order deliveries |
| title_full | A bi-criterion sequence-dependent scheduling problem with order deliveries |
| title_fullStr | A bi-criterion sequence-dependent scheduling problem with order deliveries |
| title_full_unstemmed | A bi-criterion sequence-dependent scheduling problem with order deliveries |
| title_short | A bi-criterion sequence-dependent scheduling problem with order deliveries |
| title_sort | bi criterion sequence dependent scheduling problem with order deliveries |
| topic | Scheduling Sequence-dependent Branch-and-bound Genetic algorithm Setup time Customer order scheduling |
| url | https://peerj.com/articles/cs-1763.pdf |
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