The choice of distribution route for vehicle with perishable fresh goods is not only affected by various factors such as the type of goods, the change of refrigeration environment, vehicle capacity limit and delivery time, but also needs to reach the certain targets such as the least cost and the highest customer satisfaction. In order to solve the problem, a multi-objective model for Vehicle Routing Problem (VRP) of perishable fresh goods was constructed and an improved hybrid bat algorithm was proposed to solve the constructed model. Firstly, the time window fuzzy processing method was used to define the customer satisfaction function, and the multi-objective model of optimal path selection was established by subdividing the perishable fresh goods types and defining the refrigeration cost. The bat algorithm is easy to fall into local optimum and premature convergence in solving discrete problems. Then, on the basis of analyzing the above problems, the speed update formula of classical bat algorithm was simplified, and the singlepoint or multipoint mutation selection mechanism of the hybrid bat algorithm was set up to improve the performance of the algorithm. Finally, the performance of the proposed algorithm was tested. Compared with the basic bat algorithm and several existing hybrid bat algorithms, the customer satisfaction of the proposed improved hybrid bat algorithm is improved by 1.6%-4.2% in solving VRP and the average total cost is reduced by 0.68%-2.91%. The proposed algorithm has better computational performance, higher computational efficiency and stability.