Integrated supply-demand models for the optimization of flexible transportation systems

This thesis investigates methodologies for improving the demand responsiveness of transportation systems through flexibility. The methodologies propose advances both in demand and supply models having a focus on supply-demand interactions. The demand side enables to understand the underlying travel behavior and is important to identify the most important aspects of flexibility that needs to be offered with new transportation alternatives. Supply models that integrate supply-demand interactions lead to more efficient and flexible decision support tools with integrated decision problems. Furthermore the supply models enable to understand the impact of flexibility on transportation operations with appropriate representation of flexibility aspects. The main study area of the thesis is air transportation however we believe that the methodological contributions of the thesis are not limited to any mode and have the potential to provide improvements in various systems. In the context of demand modeling, advanced demand models are studied. In the first place, hybrid choice models are developed in the context of a mode choice study motivated by a rich data set. Attitudes and perceptions of individuals are integrated in choice modeling framework and an enhanced understanding of preferences is obtained. Secondly, an air itinerary choice model is developed based on a real dataset. A mixed revealed preferences (RP) and stated preferences (SP) dataset is used for the estimation of the demand model. A demand model is obtained with reasonable demand elasticities due to the existence of the SP data. Advances in demand models can be exploited early in the planning phase when deciding on the capacity. For this matter an integrated airline scheduling, fleeting and pricing model is studied with explicit supply-demand interactions represented by the air itinerary choice model. The integrated model simultaneously decides on schedule design, fleet assignment, pricing, spill, and seat allocation to each class. Several scenarios are analyzed in order to understand the added-value of the integrated model. It is observed that the simultaneous decisions on capacity and revenue bring flexibility in decision making and provide higher profitability compared to state-of-the art models. The main reference model is called the sequential approach that solves the planning and revenue problems sequentially representing the current practice of airlines. The explicit integration of the demand model brings nonlinearities which cannot be characterized as convexity/concavity. For the solution of the model a heuristic method is implemented which iteratively solves two sub-problems of the integrated model. The first sub-problem is an integrated schedule planning model with fixed prices and the second sub-problem is a revenue management problem with fixed capacity. The heuristic is found to provide better quality feasible solutions, in considerably reduced computational time, compared to the