Journal of the Operations Research Society of China ›› 2021, Vol. 9 ›› Issue (4): 909-914.doi: 10.1007/s40305-020-00334-5

• • 上一篇    

  

  • 收稿日期:2019-03-25 修回日期:2020-04-14 出版日期:2021-12-30 发布日期:2021-11-25
  • 基金资助:
    This work was supported by Key Research Project of Henan Higher Education Institutions (No. 20A110003) and Project for Henan Overseas Students in 2020 and the National Natural Science Foundation of China (No. 12001169).

Unbounded Serial-Batching Scheduling on Hierarchical Optimization

Cheng He, Hao Lin, Li Li   

  1. School of Science, Henan University of Technology, Zhengzhou 450001, China
  • Received:2019-03-25 Revised:2020-04-14 Online:2021-12-30 Published:2021-11-25
  • Contact: Cheng He, Hao Lin, Li Li E-mail:hech202@163.com;linhao1974@163.com;1075351487@qq.com

Abstract: The paper considers a serial-batching scheduling problem on hierarchical optimization with two regular maximum costs, where hierarchical optimization means the primary objective function is minimized, and keeping the minimum value of the primary objective function, the secondary objective function is also minimized. In serial-batching machine environment, the machine processes the jobs in batch, and the jobs in the identical batch are processed by entering into the machine together and leaving the machine together. The time taken to process a batch amounts to the total processing time of the jobs in the batch. Moreover, a fixed switching time s is inserted when a machine begins to process a new batch. We only study the unbounded model, i.e., the batch capacity is unbounded. We give an algorithm that can solve the hierarchical optimization problem in $O\left(n^{4}\right)$ time, where n denotes the number of jobs.

Key words: Hierarchical scheduling, Serial-batching, Maximum cost

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