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A bi-criterion sequence-dependent scheduling problem with order deliveries.
Xu, Jian-You; Lin, Win-Chin; Hu, Kai-Xiang; Chang, Yu-Wei; Wu, Wen-Hsiang; Hsu, Peng-Hsiang; Wu, Tsung-Hsien; Wu, Chin-Chia.
Afiliación
  • Xu JY; College of Information Science and Engineering, Northeastern University, Shenyang, China.
  • Lin WC; Department of Statistics, Feng Chia University, Taichung, Taiwan.
  • Hu KX; Department of Statistics, Feng Chia University, Taichung, Taiwan.
  • Chang YW; Department of Statistics, Feng Chia University, Taichung, Taiwan.
  • Wu WH; Department of Healthcare Management, Yuanpei University of Medical Technology, Hsinchu, Taiwan.
  • Hsu PH; Department of Business Admistration, University of Kang-Ning, Taipei, Taiwan.
  • Wu TH; Bachelor's Program in Business Management, Fu Jen Catholic University, New Taipei City, Taiwan.
  • Wu CC; Department of Statistics, Feng Chia University, Taichung, Taiwan.
PeerJ Comput Sci ; 10: e1763, 2024.
Article en En | MEDLINE | ID: mdl-38196963
ABSTRACT
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: PeerJ Comput Sci Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: PeerJ Comput Sci Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos