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

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  • Janiak, Adam
  • Rudek, RadosLaw

Abstract

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
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    References listed on IDEAS

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    Cited by:

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    2. Bai, Danyu & Tang, Mengqian & Zhang, Zhi-Hai & Santibanez-Gonzalez, Ernesto DR, 2018. "Flow shop learning effect scheduling problem with release dates," Omega, Elsevier, vol. 78(C), pages 21-38.
    3. Lee, Wen-Chiung & Chung, Yu-Hsiang, 2013. "Permutation flowshop scheduling to minimize the total tardiness with learning effects," International Journal of Production Economics, Elsevier, vol. 141(1), pages 327-334.
    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.
    5. Heuser, Patricia & Tauer, Björn, 2023. "Single-machine scheduling with product category-based learning and forgetting effects," Omega, Elsevier, vol. 115(C).
    6. 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.
    7. Lai, Peng-Jen & Lee, Wen-Chiung, 2011. "Single-machine scheduling with general sum-of-processing-time-based and position-based learning effects," Omega, Elsevier, vol. 39(5), pages 467-471, October.
    8. 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.
    9. Sterna, Malgorzata, 2011. "A survey of scheduling problems with late work criteria," Omega, Elsevier, vol. 39(2), pages 120-129, April.

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