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

Adam Janiak , Radosław Rudek


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.
Author Adam Janiak
Adam Janiak,,
, Radosław Rudek (MISaF / IBI / DIT)
Radosław Rudek,,
- Department of Information Technologies
Journal seriesOmega - International Journal of Management Science, ISSN 0305-0483, (A 45 pkt)
Issue year2010
Publication size in sheets0.4
Keywords in Englishscheduling, learning effect, single machine, computational complexity
URL http://www.sciencedirect.com/science/article/pii/S030504830900067X
Languageen angielski
Score (nominal)40
Citation count*57 (2020-08-07)
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