IDEAS home Printed from
   My bibliography  Save this article

A note on a makespan minimization problem with a multi-ability learning effect


  • Janiak, Adam
  • Rudek, RadosLaw


In the scheduling literature the learning effect is perceived as a process of acquiring experience by a processor (e.g. a human worker) in one ability. However, in many real-life problems the processor, during execution of jobs, increases its experience in different, very often independent, abilities (skills). In consequence, it causes the overall growth of the efficiency of the processor. According to this observation, in this paper, we bring into scheduling a new approach called multi-ability learning that generalizes the existing ones and models more precisely real-life settings. On this basis, we focus on a makespan minimization problem with the proposed learning model and provide optimal polynomial time algorithms for its special cases, which often occur in management.

Suggested Citation

  • Janiak, Adam & Rudek, RadosLaw, 2010. "A note on a makespan minimization problem with a multi-ability learning effect," Omega, Elsevier, vol. 38(3-4), pages 213-217, June.
  • Handle: RePEc:eee:jomega:v:38:y:2010:i:3-4:p:213-217

    Download full text from publisher

    File URL:
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    1. 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.
    2. Wang, F. -K. & Lee, W., 2001. "Learning curve analysis in total productive maintenance," Omega, Elsevier, vol. 29(6), pages 491-499, December.
    3. 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.
    4. Fosfuri, Andrea & Tribø, Josep A., 2008. "Exploring the antecedents of potential absorptive capacity and its impact on innovation performance," Omega, Elsevier, vol. 36(2), pages 173-187, April.
    5. Chua, Ai Ling & Pan, Shan L., 2008. "Knowledge transfer and organizational learning in IS offshore sourcing," Omega, Elsevier, vol. 36(2), pages 267-281, April.
    6. Lee, Wen-Chiung & Wu, Chin-Chia & Hsu, Peng-Hsiang, 2010. "A single-machine learning effect scheduling problem with release times," Omega, Elsevier, vol. 38(1-2), pages 3-11, February.
    7. Chen, Jen-Shiang, 2008. "Optimization models for the tool change scheduling problem," Omega, Elsevier, vol. 36(5), pages 888-894, October.
    8. Wang, Ji-Bo, 2007. "Single-machine scheduling problems with the effects of learning and deterioration," Omega, Elsevier, vol. 35(4), pages 397-402, August.
    9. Mosheiov, Gur, 2001. "Scheduling problems with a learning effect," European Journal of Operational Research, Elsevier, vol. 132(3), pages 687-693, August.
    10. Hsu, Chin-Chun & Pereira, Arun, 2008. "Internationalization and performance: The moderating effects of organizational learning," Omega, Elsevier, vol. 36(2), pages 188-205, April.
    11. Potts, Chris N. & Kovalyov, Mikhail Y., 2000. "Scheduling with batching: A review," European Journal of Operational Research, Elsevier, vol. 120(2), pages 228-249, January.
    12. Chen, Wen-Jinn, 2009. "Minimizing number of tardy jobs on a single machine subject to periodic maintenance," Omega, Elsevier, vol. 37(3), pages 591-599, June.
    13. 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.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Chen, Xi & Thomas, Barrett W. & Hewitt, Mike, 2016. "The technician routing problem with experience-based service times," Omega, Elsevier, vol. 61(C), pages 49-61.
    2. Sáenz-Royo, Carlos & Salas-Fumás, Vicente, 2013. "Learning to learn and productivity growth: Evidence from a new car-assembly plant," Omega, Elsevier, vol. 41(2), pages 336-344.
    3. Sterna, Malgorzata, 2011. "A survey of scheduling problems with late work criteria," Omega, Elsevier, vol. 39(2), pages 120-129, April.
    4. De Bruecker, Philippe & Van den Bergh, Jorne & Beliën, Jeroen & Demeulemeester, Erik, 2015. "Workforce planning incorporating skills: State of the art," European Journal of Operational Research, Elsevier, vol. 243(1), pages 1-16.


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jomega:v:38:y:2010:i:3-4:p:213-217. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.