With the widespread recognition of the concept of sustainable development in society,enterprises are gradually paying attention to the recycling and utilization of resources in supply chain operations.To plan resources reasonably,a mixed integer programming model for closed-loop supply chain considering the participation of multiple entities was constructed with the total cost of the supply chain as the goal.Further considering the purchase price uncertainty,combined with distributionally robust optimization methods,data-driven fuzzy sets were used to simulate the true distribution of uncertain parameters,the mean-CVaR method was incorporated to measure the risk aversion characteristics of decision-makers,and the model was transformed into a manageable linear problem through duality theory.Then,the Gurobi solver was called in Python to solve the model,and the results show that distributionally robust optimization can effectively handle the impact of uncertain parameters in the decision-making process,and the model can provide support for decisions under different decision preferences and target budgets.Finally,the practicality of the model was verified again through sensitivity analysis.
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