Comparisons of interactive fuzzy programming approaches for closed-loop supply chain network design under uncertainty

Abstract

Abstract A closed-loop supply chain network design is a facility location problem combined with forward and reverse logistics. To reflect the environmental fluctuations and the market competitiveness, recycled products will be remanufactured and sold to obtain the advantages of achieving green environmental protection and of reducing cost. This study considers the uncertain factors such as the quantity of customer product demand, the quantity of recycled used products, and the facility opening cost to design a fuzzy mixed-integer linear programming model for a closed-loop supply chain network design under uncertainty. A two-stage interactive possibilistic programming procedure is constructed to obtain a preferred compromise solution. Four fuzzy optimization approaches are embedded into the two-stage interactive possibilistic programming model and are compared. After computing experimental testing, we find that this study, based on the TH fuzzy approach, obtains a more efficient balanced compromise solution than other fuzzy approaches.