Advances in aviation technology including the development of relatively cheap, very light jets and the possibility of free-flight have led to the realization of a per-seat, on-demand (PSOD) air transportation business that operates without a published flight schedule. This thesis addresses two fundamental planning problems motivated by the operations of PSOD air transportation. The first problem focuses on the scheduled maintenance of the fleet that has to be done periodically for safety and efficiency. The second problem is concerned with selecting locations for bases and determining how many jets to allocate to each base where bases are airports with hangar space to keep jets overnight. These decisions have a significant impact on the ability of the business to accommodate transportation requests and also to satisfy these requests efficiently.;In the first part of the thesis, we study tactical decision making for scheduled maintenance planning that determines the daily maintenance capacities, i.e. the maximum number of jets that can be maintained on a day. These decisions are made for two operating conditions: a growth phase where jets are introduced gradually into the system and steady state where the fleet size is constant. We model the tactical maintenance capacity planning during the growth phase as an integer program and develop an optimization-based local search to solve the problem. We present a computational study that investigates the impact of the frequency in which jets are introduced into the system on the maintenance capacity. The results illustrate that around 14% less overall capacity is needed when jets are introduced more frequently in smaller batches. Tactical planning for scheduled maintenance of PSOD air transportation in the steady state is NP-hard. We analyze a special case of this problem for which we can determine the optimal and the long run capacities with a pseudo-polynomial time algorithm.;In the second part of the thesis, we address the operational planning for scheduled maintenance. Operational level planning 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 their proximity to the next maintenance. The methodology can effectively schedule maintenance of 480 jets over a two year planning horizon where the decisions for a single day can be made on average within 12 seconds. Furthermore, an average capacity usage rate of 96% together with less than 1% infeasible maintenance indicate a good match between the capacities set at the tactical and the operational maintenance needs. We further develop an integrated framework in order to capture the interaction between the operational level maintenance decisions and flight scheduling. A simulated case study for the operations of a PSOD air transportation provider, DayJet Corporation, demonstrates that only 6% of the maintenance activities have to be delayed by on average one day to accommodate the requirements of the 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 amongst these bases are made. We first present a solution approach in which the information about travel demand (in the form of transportation requests) and 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. Thus, the information about travel demand and flight scheduling is captured in more detail compared to the traditional facility location problem. The results of our computational study illustrate that an average of 2% increase in the acceptance rate for transportation requests, and an average of 4% decrease in the average daily flying time can be achieved when travel demand and flight scheduling are captured in more detail while making base location and fleet allocation decisions.
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