The p-hub center location problem aims to locate p hubs and allocate other nodes to these hub n- odes in order to minimize the maximal travel time. It is more important for time-sensitive distribution systems. Due to the presence of uncertainty, more researches are recently focused on the problem in non- deterministic environment. This paper joins the research stream by considering travel times as uncertain variables instead of random variables or fuzzy ones. The goal is to model the p-hub center problem based on experts subjective belief in the case of lack of data. The uncertain distribution of the maximal travel time is first derived and then a chance constrained programming model is formulated. The deterministic equivalent forms are further given when the information of uncertainty distributions is provided. A hy- brid intelligent algorithm is designed to solve the proposed models and numerical examples are presented to illustrate the application of this approach and the efectiveness of the algorithm.