With the changing climates, numerous broadly defined logistical depots ranging from air and sea ports to bus and train stations all suffer from volatile repair and maintenance costs that are fluctuating and on average increasing over time. At the same time, human-made (i.e., typically governments) policies often influences the repair and maintenance costs as well (e.g., the environmentally friendly disposal policies for the repair and maintenance components). Under these circumstances, we first construct stochastic control models based on binomial lattices when the repair and maintenance costs are following geometric Brownian motion processes while the human-made policies follow Poisson jump processes. From the subsequent analyses, we aim to produce economic implications and managerial insights so as to enhance decision and policy making such as whether and when to expand, contract, mothball, and/or decommission such logistical depots. By conducting a numerical study on the airport re-location, we empirically show how to derive the most economically rational strategy, and to determine the optimal re-location time.