A novel robust fuzzy programming approach for closed loop supply chain design

Abstract: In recent decade, the increasing importance of economic benefits and environmental impacts of using scrapped products has encouraged most companies to focus on the closed-loop supply chain (CLSC) design. This paper considers the problem of CLSC network design under fuzzy uncertain conditions. The uncertain source is that the values of these parameters are usually imprecise and can be specified by possibilistic variables. To handle the uncertainty, a possibilistic programming approach is an appropriate method of incorporating such uncertainty In this problem. Possibility theory is applied to choose such solution in such a problem and a robust fuzzy programming (RFP) approach is proposed. In the proposed model, the best robust decision has the additional property in terms of mean value and variability of the objective function named possibilistic variability. The performance of the proposed RFP model is also compared with that of mean model in term of the variability and mean cost of model.