Site planning for parks consists of synthetic strategies to improve visitors' experience and appreciation of park features. An important aspect in site planning is to coordinate visitor flows in order to avoid excessive congestion that may depreciate visiting experience. An emerging need in the coordination strategies is to personalize visiting routes and enhance the enjoyment of the tour for individual visitors. On the individual level, visitors have diverse preferences for park attractions. Scheduling a tour to visit attractions is restricted by not only the layout of park facilities but also the uncertainty of waiting induced by different lengths of lines at attractions. This paper proposes a tentative solution to optimize the logistics of individual tours by considering the dynamic nature of waiting time at park attractions derived from empirical data. The optimal solution is achieved using the branch-and-bound algorithm and is implemented in a real-world case of Beijing Zoo, a metropolitan zoology park in Beijing, China. The case study provides corroborating evidence for studying the logistical routing of park tours that: (1) visitors arriving at the park earlier can avoid crowds and excessive lines whereas visiting at midday would encounter excessive waiting and (2) the shortest tour route may not necessarily be the most efficient; strategically scheduling the visit to popular exhibits in their off-peak hours could effectively shorten overall tour time. This problem, called the Traveling Salesman Problem with Waiting Times (TSPWT) increases the realism of the routing problem while shedding new light on personalized routing strategies for improving individual touring experience.