Tourists expect to get travel experiences like low-cost, convenient itinerary, high comfort and so on.Meanwhile, they have different tourist interests such as history and culture, natural landscape, food and shopping, etc.Therefore, a personalized travel route recommendation method based on an improved shuffled frog leaping algorithm is proposed in this paper.A model is established to optimize the personalized travel route recommendation problem, and an improved shuffled frog leaping algorithm is designed based on the characteristics of the model.By adjusting the controllable accuracy, incorporating new selection criteria and handling abnormal solutions in time, the population diversity is increased and the risk of missing the optimal solution is reduced, which enhance the local search ability and searching accuracy of the algorithm.The personalized travel route recommendation for three-day tour in Nanjing is taken as an instance to verify the proposed method.Relevant data are collected, including admission fees, opening hours, and accommodation expenses for well-known tourist attractions in Nanjing.The results show that compared with basic shuffled frog leaping algorithm, the proposed method can recommend touring routes with higher accuracy and better meet the users' individual interests.