an inexact-fuzzy-stochastic optimization model for a closed loop supply chain network design problem

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 and the complex interactions among various uncertain parameters are challenging the capabilities of the developed tools. the aim of this paper, therefore, is to propose a new mathematical model for designing a clsc network that integrates the network design decisions in both forward and reverse supply chain networks. moreover, another objective of this research is to introduce an inexact-fuzzy-stochastic solution methodology to deal with various uncertainties in the proposed model. computational experiments are provided to demonstrate the applicability of the proposed model in the clsc network design.