A multi-objective model to configure an electronic reverse logistics network and third party selection

The application of reverse logistics (RL) is expanded prominently due to environmental issues, and profit related to the returned products. RL includes all activities associated with product recovery such as repairing, recycling, remanufacturing, and disposing. Several partners are required to collaborate efficiently on account of obtaining optimal outcomes. In this sense, the selection of partners in RL can be considered as a multi-criteria decision making (MCDM) problem. In this research, it is aimed to apply fuzzy analytic network process (FANP) to convert the environmental qualitative factors to the quantitative parameters. Furthermore, an optimization model consisting of multiple echelons, components, and products is introduced for the RL in multiple periods. A multi-objective mixed-integer linear (MILP) programming model is employed to maximize the total profit, green practices, and on-time delivery with minimization of defect rate in the proposed RL. Finally, the multi-objective model is solved to achieve non-dominated solutions between the objectives. The proposed method is helpful in selection of the best third party reverse logistics provider.