A DECISION MODEL FOR REVERSE LOGISTICS SERVICE PROVIDERS IN DETERMINING ROBUST OPTIMAL PROCESSING QUANTITIES OF RETURNED PRODUCTS

Reverse logistics covers a serial of activities in dealing with returned products from consumers, including collecting, reusing and recycling. Implementing reverse logistics is much more complicated and expensive than forward logistics to an enterprise. Meanwhile, the systematic patterns for handling transportation, storage, processing and management processes of these activities are still called for. Consequently, to reduce the reverse logistics cost and focus on its core business, an enterprise prefers outsourcing these activities in this manner. Previous studies focused on the selection of processing facilities and the infrastructure design of reverse logistics distribution channels for third-party reverse logistics service providers. In contrast, this research aims to deal with the issues of reverse logistics from different viewpoint. We propose a decision model for a reverse logistics service provider under the context of uncertain, multi-period, multi-type returned/recycled products and multiple processing facilities environment. The major focus of this model is on determining the robust optimal quantities of customer orders and robust optimal processing quantities of returned products for each processing facility. To deal with the issues of uncertainties, the model applies the scenario-based robust optimization approach. Further information on experiment results and implications can be found in this paper.