| Summary: | Reverse logistics/closed loop supply chain management has become a hot topic of discussion since the last decade. This trend is created by different forces such as economical, environmental and customers concerns which enable companies to seek the appreciate strategies to fit the vary returns and get the profitable of reuse activities.
This study tries to find the optimal recovery value for different situations through analytical models. The reasons for developing analytical models are due to the wide range of usage, which is not only for specifically industries, but also the observable to give the multiple factors a good explanation. Consequently, the analytical models have been applied to develop the optimal recovery policies, dealing with the fluctuation of returns, such as the uncertainty of quality and quantity. Moreover, we also examine the threshold of returns’ quality and help decision makers to determine the best sorting policies for the returns. In this thesis, the best sorting policies are defined as the minimum total cost of taking recovery process. Finally, we find that the more options provided to companies, the more complicated optimum strategies are. The related factors involved in this study are the return rate (
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