Concerning the high frequency logistics distribution of fresh products due to the products' perishability and vulnerability, as well as the uncertainty of demand and return, a multi-period closed-loop logistics network for fresh products with fuzzy variables was constructed to achieve the multi-decision arrangement of minimum system cost, optimal facility location and optimal delivery route. In order to solve the Fuzzy Mixed Integer Linear Programming (FMILP) model corresponding to the system, firstly, the amounts of demand and return were defined as triangular fuzzy parameters; secondly, the fuzzy constraints were transformed into crisp formula by using fuzzy chance constrained programming method; finally, the optimal solution of case was obtained by using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithm. The experimental results show that multi-period closed-loop system performs better than single-period system in the aspect of multi-decision programming, meanwhile, the confidence levels of triangular fuzzy parameters have significant influence on the optimal operation of enterprise, thus providing a reference for relevant decision makers.