Abstract

The rise of electronic commerce and the stricter government regulations on the recovery of end-of-life products increased the number of products returned by customers. A company may deal with increasing product returns by developing its own reverse logistic system. However, high fixed costs associated with dedicated reverse logistics equipment and infrastructure force many companies to outsource their reverse logistics operations to third-party reverse logistics providers. One of the important problems faced by third-party reverse logistics providers is the selection of the types of used products to be collected. In this study, a four-phase used product selection methodology is proposed. First, the quantitative and qualitative selection criteria are determined. Then the weights of the criteria are calculated using fuzzy analytic hierarchy process. Next, simulation models are employed to determine the values of quantitative criteria. Finally, technique for order preference by similarity to ideal solution ranks alternative used product types. A numerical example is also provided in order to present the applicability of the proposed methodology.

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