An axiomatic design approach to the classification of reverse logistics network design studies under fuzziness

Reverse logistics (RL) is recently receiving much attention because of growing environmental problems. Reusing, recycling and remanufacturing are considered as environmentally and financially effective processes for various drivers - government, corporations and customers. Because many parameters have to be defined by decision makers based on their experiences in RL, a significant number of articles that apply fuzzy set theory have been written in the relevant literature. This paper proposes a model with an axiomatic design (AD) approach on the subject of RL and analyzes the fuzzy set theory used models in relation to steps defined in AD model. AD is applied to generate a conceptual framework for RL network design by distinguishing objectives and means of RL at different levels. The model proposed in this study can be used as a road map for both organizations needing to enhance an existing network, organizations intending to design a network from the beginning and researchers who want to advance in their RL studies by using fuzzy based models.