Using a novel hybrid method based on fuzzy dematel and fuzzy group topsis for suppliers selection in reverse logistics network

Many companies are unable or unwilling to perform all activities of reverse logistics. Therefore, these companies assign all or some of these activities to resources (suppliers) from outside of the company. Hence, proper selection of suppliers in reverse logistics can reduce or even eliminate large amount of future problems in this area. The best supplier in reverse logistics is selected by a group of decision makers through evaluating some of conflicting criteria. These criteria are linguistic variables and they need to be quantified by giving weight to them in fuzzy environment. This research is to develop an integrated method for selecting suppliers in a way that reverse logistics requirements are also included .In this study, after identification of criteria we use the fuzzy DEMATEL approach to measure the relationships between the criteria and then, we determine the parameters associated with each option in each criterion to use them in a fuzzy group TOPSIS method in order to prioritize items by similarity to ideal solution. And finally, the best supplier will be chosen from a set of potential suppliers. A case study is given to show the influence of the proposed method.