Design of An Integrated Robust Optimization Model for Closed-Loop Supply Chain and supplier and remanufacturing subcontractor selection

The development of optimization and mathematical models for closed loop supply chain (CLSC) design has attracted considerable interest over the past decades. However, the uncertainties that are inherent in the network design are challenging the capabilities of the developed tools. In CLSC Uncertainty in demand is major source of uncertainty. The aim of this paper, therefore, is to present a Robust mathematical model for designing a CLSC network under uncertain customer demands that integrates the network design decisions in both forward and reverse supply chain networks. Two phase approach, is proposed for this purpose. In the first phase, due to extremely important task of Suppliers Selection in purchasing and supply chain management, a fuzzy method is utilized to evaluate suppliers based on quantitative and qualitative criteria. The output of this stage is the weight of each supplier according to each part which taken into account as input of next phase. in the second phase, we propose a Multi Objective Mixed-Integer linear Programming model  to determine the optimal number of part and products in CLSC network. Results have revealed that the model is capable of controlling the network uncertainties as a result of which a robustness price will be imposed on the system.