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Single-Machine Scheduling with Learning Effects and Maintenance: A Methodological Note on Some Polynomial-Time Solvable Cases

机译:具有学习效果和维持能力的单机调度:一些多项式时间可解案例的方法论注释

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摘要

This work addresses four single-machine scheduling problems (SMSPs) with learning effects and variable maintenance activity. The processing times of the jobs are simultaneously determined by a decreasing function of their corresponding scheduled positions and the sum of the processing times of the already processed jobs. Maintenance activity must start before a deadline and its duration increases with the starting time of the maintenance activity. This work proposes a polynomial-time algorithm for optimally solving two SMSPs to minimize the total completion time and the total tardiness with a common due date.
机译:这项工作解决了具有学习效果和可变维护活动的四个单机调度问题(SMSP)。作业的处理时间同时由其相应的计划位置的递减函数和已处理作业的处理时间之和确定。维护活动必须在截止日期之前开始,并且持续时间会随着维护活动的开始时间而增加。这项工作提出了一种多项式时间算法,用于最优地求解两个SMSP,以最大程度地缩短总完成时间和总拖延时间(具有共同的到期日)。

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  • 来源
    《Mathematical Problems in Engineering》 |2017年第7期|7532174.1-7532174.6|共6页
  • 作者单位

    Natl Taipei Univ Technol, Dept Ind Engn & Management, Taipei, Taiwan;

    Natl Chiao Tung Univ, Dept Transportat & Logist Management, Taipei, Taiwan;

    Chang Gung Univ, Dept Informat Management, Taoyuan, Taiwan|Ming Chi Univ Technol, Dept Ind Engn & Management, Taipei, Taiwan|Linkou Chang Gung Mem Hosp, Dept Neurol, Taoyuan, Taiwan;

    Wistron Corp, Taipei, Taiwan;

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