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Single-machine scheduling problems with actual time-dependent and job-dependent learning effect

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  • Jiang, Zhongyi
  • Chen, Fangfang
  • Kang, Huiyan

Abstract

In this study, we introduce an actual time-dependent and job-dependent learning effect into single-machine scheduling problems. We show that the complexity results of the makespan minimization problem and the sum of weighted completion time minimization problem are all NP-hard. The complexity result of the maximum lateness minimization problem is NP-hard in the strong sense. We also provide three special cases which can be solved by polynomial time algorithms.

Suggested Citation

  • Jiang, Zhongyi & Chen, Fangfang & Kang, Huiyan, 2013. "Single-machine scheduling problems with actual time-dependent and job-dependent learning effect," European Journal of Operational Research, Elsevier, vol. 227(1), pages 76-80.
    • Handle: RePEc:eee:ejores:v:227:y:2013:i:1:p:76-80
    DOI: 10.1016/j.ejor.2012.12.007
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    References listed on IDEAS

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    1. Koulamas, Christos & Kyparisis, George J., 2007. "Single-machine and two-machine flowshop scheduling with general learning functions," European Journal of Operational Research, Elsevier, vol. 178(2), pages 402-407, April.
    2. G Mosheiov & J B Sidney, 2005. "Note on scheduling with general learning curves to minimize the number of tardy jobs," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(1), pages 110-112, January.
    3. Biskup, Dirk, 1999. "Single-machine scheduling with learning considerations," European Journal of Operational Research, Elsevier, vol. 115(1), pages 173-178, May.
    4. D-L Yang & W-H Kuo, 2007. "Single-machine scheduling with an actual time-dependent learning effect," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(10), pages 1348-1353, October.
    5. Mosheiov, Gur & Sidney, Jeffrey B., 2003. "Scheduling with general job-dependent learning curves," European Journal of Operational Research, Elsevier, vol. 147(3), pages 665-670, June.
    6. Biskup, Dirk, 2008. "A state-of-the-art review on scheduling with learning effects," European Journal of Operational Research, Elsevier, vol. 188(2), pages 315-329, July.
    7. Kuo, Wen-Hung & Yang, Dar-Li, 2006. "Minimizing the total completion time in a single-machine scheduling problem with a time-dependent learning effect," European Journal of Operational Research, Elsevier, vol. 174(2), pages 1184-1190, October.
    8. Cheng, T. C. E. & Ding, Q. & Lin, B. M. T., 2004. "A concise survey of scheduling with time-dependent processing times," European Journal of Operational Research, Elsevier, vol. 152(1), pages 1-13, January.
    9. Wang, J.-B. & Ng, C.T. & Cheng, T.C.E. & Liu, L.L., 2008. "Single-machine scheduling with a time-dependent learning effect," International Journal of Production Economics, Elsevier, vol. 111(2), pages 802-811, February.
    10. T.C. Cheng & Guoqing Wang, 2000. "Single Machine Scheduling with Learning Effect Considerations," Annals of Operations Research, Springer, vol. 98(1), pages 273-290, December.
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    Citations

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    Cited by:

    1. Derya Deliktaş, 2022. "Self-adaptive memetic algorithms for multi-objective single machine learning-effect scheduling problems with release times," Flexible Services and Manufacturing Journal, Springer, vol. 34(3), pages 748-784, September.
    2. Janiak, Adam & Janiak, Władysław A. & Krysiak, Tomasz & Kwiatkowski, Tomasz, 2015. "A survey on scheduling problems with due windows," European Journal of Operational Research, Elsevier, vol. 242(2), pages 347-357.
    3. Heuser, Patricia & Tauer, Björn, 2023. "Single-machine scheduling with product category-based learning and forgetting effects," Omega, Elsevier, vol. 115(C).
    4. Zhongyi Jiang & Fangfang Chen & Xiandong Zhang, 2022. "Single-machine scheduling problems with general truncated sum-of-actual-processing-time-based learning effect," Journal of Combinatorial Optimization, Springer, vol. 43(1), pages 116-139, January.
    5. Cheng, T.C.E. & Shafransky, Y. & Ng, C.T., 2016. "An alternative approach for proving the NP-hardness of optimization problems," European Journal of Operational Research, Elsevier, vol. 248(1), pages 52-58.

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