This thesis addresses two planning problems motivated by the operations of PSOD air transportation: scheduled maintenance planning, and base location and fleet allocation. In the first part of the thesis, we study tactical planning for scheduled maintenance which determines the daily maintenance capacities for two operating conditions: a growth phase and the steady state. We model tactical maintenance capacity planning during the growth phase as an integer program and develop an optimization-based local search to solve the problem. Tactical planning of steady state maintenance capacity concerns a special case for which we determine the optimal and the long run capacities with a pseudo-polynomial time algorithm. In the second part of the thesis, we address operational planning for scheduled maintenance which is concerned with assigning itineraries to jets and determining the specific jets to be scheduled for maintenance on a daily basis given a certain maintenance capacity. We present a solution methodology that employs a look-ahead approach to consider the impact of our current decisions on the future and decomposes the problem exploiting the differences between jets with respect to the proximity to their next maintenance. We further develop an integrated framework in order to capture the interaction between operational level maintenance decisions and flight scheduling. In the third and final part of the thesis, we present the tactical level base location and fleet allocation problem. As PSOD air transportation experiences changes in travel demand and fleet size, decisions regarding where to open new bases and how to allocate the number of jets among the bases are made. We first present a solution approach in which high level information about flight scheduling is used in a traditional facility location problem. We next develop a model that works directly with transportation requests and integrates a simplified version of flight scheduling with the base location and fleet allocation decisions in order to capture more detail.