Abstract：With the consideration of high losses, large amount of carbon emission, neglect of social benefits and uncertain returns in the fresh product logistics network, a fuzzy multi-objective optimization model for the sustainable closed-loop fresh product logistics network under fuzzy environment is established aiming at the minimum economic cost, minimum environmental impact and maximum social benefits. In order to solve the model, a priority-based genetic code is written. The improved genetic algorithm and CPLEX are used to solve a fresh food enterprise in Shanghai respectively. The feasibility of the model and the effectiveness of the improved genetic algorithm (GA) are verified by example analysis and algorithm comparison. Furthermore, the results under different confidence levels of triangular fuzzy quantity of returned products are compared and analyzed. The results show that the satisfaction degree of multi-objective optimization is greater than that of single-objective optimization, and the confidence level of triangular fuzzy quantity has a significant impact on the optimal operation of enterprises.
