<p>In transportation systems with mobile and modular facilities, how to make decisions related to facility location and capacity management during the planning horizon is critical; since the effective parameters in making these decisions change over time, it is required to adjust the locations and facilities’ operational capacity within the planning horizon to coordinate with the changing parameters. This paper presents a nonlinear programming formulation for a dynamic, modular, planar hub location problem when transportation demand is stochastic and its change in a continuous-time planning horizon is time-dependent. A dynamic programming-based hybrid solution method is presented to the proposed model, in which some polynomial-time algorithms (drop &amp; interchange, simple allocation, allocation improvement, Hyperboloid Approximation Procedure (HAP), and cost calculation) are used to calculate the cost of decisions in different states. The results of instances on the Australian Postal network (AP) dataset with up to a hundred nodes and eight hubs and sensitivity analysis are reported. The findings demonstrate that in the uncertain case, the total selected capacity for each hub in the entire planning horizon is more than in the case where the uncertain parameters take their mean value.</p>