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- W2019244003 abstract "Recently, learning effects in scheduling problems have received growing attention. The position-based learning model seems to be a realistic assumption for the case where the actual processing of the job is mainly machine driven. In this paper, we consider the sum-of-processing-time-based learning model. We propose a learning model which considers both the machine and human learning effects, simultaneously. We first show that the position-based learning and the sum-of-processing-time-based learning models in the literature are special cases of the proposed model. Moreover, we present the solution procedures for some single-machine and some flowshop problems." @default.
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- W2019244003 modified "2023-10-14" @default.
- W2019244003 title "Machine scheduling problems with a general learning effect" @default.
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- W2019244003 doi "https://doi.org/10.1016/j.mcm.2009.09.001" @default.
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