Designing A Sustainable Closed Loop Supply Chain Network under Uncertainty: A Robust Possibilistic Programming Approach - Akhondi-Bajegani, Esmaeil; Torabi, S Ali (International journal of supply and operations management, 2025)
This paper studies a comprehensive multi-objective closed loop supply chain network design problem by considering economic performance, environmental impacts, and social responsibilities as the most important concerns of a supply chain's stakeholders. Due to the unavailability of historical data, all uncertain parameters are represented as fuzzy numbers based on the subjective knowledge of experts. A novel multi-objective mixed integer programming model is developed to formulate the problem. Furthermore, a robust possibilistic counterpart model is derived to generate robust solutions under epistemic uncertainty of parameters. Because of the multi-objective nature of the problem an NSGA-IT algorithm is designed to yield Pareto-optimal solutions. A case study in the automotive industry is provided to validate the developed model and its solution method. Finally, several sensitivity analyses are carried out to determine the impact of critical parameters.