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Single-machine scheduling problems with a learning effect matrix

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Abstract

Scheduling problems with learning effects have been widely studied in numerous publication. However, the learning effect might accelerate, especially in the steel plates and the human interaction systems. In this paper, we propose a new scheduling model with a learning effect matrix. We show that the makespan and the total completion time problems can be optimally solved in polynomial time. We present heuristic sequencing rules and analyze the worst-case bounds for performance ratios to minimize the total weighted completion time, the maximum lateness, and the total tardiness. We also show that these heuristic rules can be optimal under some agreeable conditions between the normal processing times and job due dates or weights.

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Acknowledgments

We thank the editors and two anonymous referees for their helpful comments on the earlier version of our paper. This work was supported by National Natural Science Foundation of China (11401065, 71371120, 61302180), the China Postdoctoral Science Foundation funded project (2013M540698, 2014T70854), the Foundation of Chongqing Education Commission (KJ130606) and The Chongqing Municipal Science and Technology Commission of Natural Science Fund Projects (cstc2014jcyjA00003). This paper was supported in part by the Ministry of Science Technology (MOST) of Taiwan under Grant Numbers MOST 105-2221- E-035-053-MY3, MOST 103-2410-H-035-022-MY2, and MOST 105-2816-H-035-001.

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Correspondence to Chin-Chia Wu.

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Zhang, X., Liu, SC., Yin, Y. et al. Single-machine scheduling problems with a learning effect matrix. Iran J Sci Technol Trans Sci 42, 1327–1335 (2018). https://doi.org/10.1007/s40995-016-0080-1

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  • DOI: https://doi.org/10.1007/s40995-016-0080-1

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