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Single-machine scheduling problems with general truncated sum-of-actual-processing-time-based learning effect
Journal of Combinatorial Optimization ( IF 1 ) Pub Date : 2021-05-08 , DOI: 10.1007/s10878-021-00752-y
Zhongyi Jiang , Fangfang Chen , Xiandong Zhang

We study single machine scheduling problems with general truncated sum-of-actual-processing-time-based learning effect. In the general truncated learning model, the actual processing time of a job is affected by the sum of actual processing times of previous jobs and by a job-dependent truncation parameter. We show that the single machine problems to minimize makespan and to minimize the sum of weighted completion times are both at least ordinary NP-hard and the single machine problem to minimize maximum lateness is strongly NP-hard. We then show polynomial solvable cases and approximation algorithms for these problems. Computational experiments are also conducted to show the effectiveness of our approximation algorithms.



中文翻译:

具有一般截断的实际处理时间和学习效果的单机调度问题

我们研究具有基于实际处理时间的总截断的学习效果的单机调度问题。在一般的截断学习模型中,作业的实际处理时间受先前作业的实际处理时间的总和以及与作业有关的截断参数的影响。我们表明,最小化制造期和最小化加权完成时间之和的单机问题至少是普通的NP-hard,而最小化最大延迟的单机问题也是强烈的NP-hard。然后,我们显示这些问题的多项式可解情况和近似算法。还进行了计算实验,以证明我们的近似算法的有效性。

更新日期:2021-05-08
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