Abstract
Organisations often outsource reverse logistics (RL) to third-party RL providers (3PRLPs) to focus on their primary business and reduce costs. The existence of multiple criteria available for choosing a 3PRLP, which are sometimes contradictory and yet related to each other, has led decision-makers to consider the development of multi-criteria decision-making models. The purpose of this study is to develop a hybrid model integrating the analytic network process (ANP) and the intuitionistic fuzzy-grey superiority and inferiority ranking (IFG-SIR) process to help an industrial production group select a 3PRLP. The ANP method is used to analyse the relationships among the different selection criteria and to obtain a weight indicating the relative importance of each criterion. The best 3PRLP is chosen using the IFG-SIR process. The classical SIR technique requires a sufficient amount of data while relying on the technique for order preference by similarity to ideal solutions and simple additive weighted methods. We use intuitionistic fuzzy sets to account for the subjectivity inherent to the potentially strategic opinions of the experts and of grey relation analysis to simplify the ranking process. We present a real-world case study to exhibit the applicability and demonstrate the efficacy of the proposed model.