Proposal of a Stochastic Programming Model for Reverse Logistics Network Design under Uncertainties

Abstract

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 paper, 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 electrical and electronic equipment 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 contribute the RLND literature by considering return quantity and quality, which is related to sorting ratio in sorting centers, uncertainties in presented model. Second contribution is to present generic recycling model with multi-product, and multi-stage for third part RL firms.