4.7 Article

No-Idle Flowshop Scheduling for Energy-Efficient Production: An Improved Optimization Framework

期刊

MATHEMATICS
卷 9, 期 12, 页码 -

出版社

MDPI
DOI: 10.3390/math9121335

关键词

production management; energy-efficiency; scheduling; no-idle flowshop; metaheuristics

资金

  1. Ministry of Science and Technology, Taiwan [MOST 109-2221-E-027-073/Most-109-2410-H-182-009-MY3]
  2. Linkou Chang Gung Memorial Hospital [BMRPA19]

向作者/读者索取更多资源

The production environment in modern industries features zero idle-time between jobs on each machine, improving energy efficiency and impacting cleaner production in other scenarios. This study developed an extended solution for optimizing the Bi-objective No-Idle Permutation Flowshop Scheduling Problem (BNIPFSP) after conducting a comprehensive literature review. Extensive numerical tests and statistical analysis revealed that the proposed extension outperformed in terms of solution quality, although at the expense of longer computational time.
Production environment in modern industries, like integrated circuits manufacturing, fiberglass processing, steelmaking, and ceramic frit, is characterized by zero idle-time between inbound and outbound jobs on every machine; this technical requirement improves energy efficiency, hence, has implications for cleaner production in other production situations. An exhaustive review of literature is first conducted to shed light on the development of no-idle flowshops. Considering the intractable nature of the problem, this research also develops an extended solution method for optimizing the Bi-objective No-Idle Permutation Flowshop Scheduling Problem (BNIPFSP). Extensive numerical tests and statistical analysis are conducted to evaluate the developed method, comparing it with the best-performing algorithm developed to solve the BNIPFSP. Overall, the proposed extension outperforms in terms of solution quality at the expense of a longer computational time. This research is concluded by providing suggestions for the future development of this understudied scheduling extension.

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