Abstract:We consider the problem of remanufacturing planning in the presence of statistical estimation errors. Determining the optimal remanufacturing timing, first and foremost, requires modeling of the state transitions of a system. The estimation of these probabilities, however, often suffers from data inadequacy and is far from accurate, resulting in serious degradation in performance.To mitigate the impacts of the uncertainty in transition probabilities, we develop a novel datadriven modeling framework for remanuf… Show more
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