基于模糊随机回收数量的逆向物流库存控制策略研究

Forecasting the quantity precisely is the key when modeling the inventory model if return is considered. Compared to demand, returned products showed greater uncertainty regarding to quality. In this regard, a new model was built considering the fuzziness and randomness simultaneously, using expectation theory of fuzzy random variable. The demands from clients were considered as normal distribution. The paper shows the optimal control variables after comparing with the traditional inventory models. At last, a numerical example and sensitivity analysis are shown to verify the validity of the model.