Modelling Product Returns in a Closed-Loop Supply Chain Under Uncertainties: A Neuro Fuzzy Approach
Returning of products is the key part of the remanufacturing process. This study proposes a methodology for product returns in a single production/remanufacturing cycle system. The presented methodology constitutes of two phases including a neuro-fuzzy approach and mathematical formulas to select an optimal inventory strategy regarding the total cost minimization. Through the approach, the relationship between both the proportions of return and reuse items and the fluctuation in total cost is investigated. Besides, qualitative factors belonging to external effects are used in determining the rate of reusable items. The methodology including the sensitivity analysis is illustrated by an example to demonstrate the effect of return items and its linkage to the optimal inventory strategy.
Keywords: Forecasting, hybrid, intelligent, inventory strategy, neuro-fuzzy, remanufacturing