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Mathematical Biosciences and Engineering

2022, Volume 19, Issue 5: 5104-5119. doi: 10.3934/mbe.2022238
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Due date assignment scheduling with positional-dependent weights and proportional setup times

  • 1.
    Business School, Northwest Normal University, Lanzhou 730070, China
  • 2.
    Department of Postal Communication and Management, Shijiazhuang Posts and Telecommunications Technical College, Shijiazhuang 050021, China

  • Academic Editor: Daniel Rossit
  • Received: 20 January 2022 Revised: 10 March 2022 Accepted: 13 March 2022 Published: 18 March 2022

  • In this paper, we investigate the single-machine scheduling problem that considers due date assignment and past-sequence-dependent setup times simultaneously. Under common (slack and different) due date assignment, the objective is to find jointly the optimal sequence and optimal due dates to minimize the weighted sum of lateness, number of early and delayed jobs, and due date cost, where the weight only depends on it's position in a sequence (i.e., a position-dependent weight). Optimal properties of the problem are given and then the polynomial time algorithm is proposed to obtain the optimal solution.

    Citation: Xuyin Wang, Weiguo Liu, Lu Li, Peizhen Zhao, Ruifeng Zhang. Due date assignment scheduling with positional-dependent weights and proportional setup times[J]. Mathematical Biosciences and Engineering, 2022, 19(5): 5104-5119. doi: 10.3934/mbe.2022238

    Related Papers:

  • In this paper, we investigate the single-machine scheduling problem that considers due date assignment and past-sequence-dependent setup times simultaneously. Under common (slack and different) due date assignment, the objective is to find jointly the optimal sequence and optimal due dates to minimize the weighted sum of lateness, number of early and delayed jobs, and due date cost, where the weight only depends on it's position in a sequence (i.e., a position-dependent weight). Optimal properties of the problem are given and then the polynomial time algorithm is proposed to obtain the optimal solution.


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