Proposal of a stochastic programming model for reverse logistics network design under uncertainties

In recent years, Reverse Logistics (RL) has received increasing attentions in supply chain management area due to the economic, political, and environmental reasons. The aim of this study is to address Reverse Logistics Network Design (RLND) problem under return quantity and quality uncertainties to minimize total cost. Uncertain parameters are one of the challenging characteristics of RL networks. In this study, a generic two stage stochastic programming model to cope with uncertainties in RLND is presented. The usefulness of the proposed model was validated by its application to third party waste of electrical and electronic equipment (WEEE) recycling firm in Turkey. The results show that the presented two stage stochastic programming model provides good solutions to make efficient decisions under quantity and quality uncertainties. In this paper, we have contributed the RLND literature by taking into consideration return quality, which is related to sorting ratio in inspection centers, and quantity uncertainties at the same time in presented model as a result of detail literature review. Second contribution is to present a generic recycling network with multi-product, and multistage for third party WEEE recycling firms.