Designing Demand-Responsive Bus Services for Imbalanced Demand

Traditional public transport systems typically operate using a fixed-route and fixed-timetable scheme. To introduce a level of flexibility to the operations and, ultimately, make public transportation more attractive, research on public transport planning and optimization shifts towards more tailored options, which we call: `demand-responsive systems'. In this thesis, we explore demand-responsive bus operations to improve the efficiency of public bus systems when there is demand imbalance. When a single bus line operating between a city center and a terminal station is considered, there exists a clear imbalance in the demand for transportation between the two directions during peak hours. We try to exploit this imbalance. We introduce the Demand-Responsive System with Express Services (DRS-ES) to increase the frequency of service in the peak direction by allowing vehicles to take an express service in the off-peak direction. Mixed Integer Quadratic Programs are developed to optimize the decisions of this system based on expected demand. Different variants of the DRS-ES are analyzed. Experiments show that the demand-responsive operation can indeed improve the average travel time of passengers. However, only small and medium-size instances can be solved to optimality due to problem complexity. Variable Neighborhood Search (VNS) algorithms are developed to optimize the operational decisions of the DRS-ES within a couple of minutes. This means that just before the peak hours, VNS algorithms can decide which buses should make an express service in the off-peak direction and when to depart from the city center and the terminal. Experiments show that the total passenger travel time improves about 10\% on average for a real-size benchmark instance as a result of the increased frequency of service in the peak direction. In fact, the improvement reaches up to 40\% especially if only waiting times are considered or in case of limited vehicle capacity. The performance of the system is also analyzed under different fleet sizes and capacities, durations of peak hours, and demand scenarios. We then propose a much more flexible and complex variant of the DRS-ES, the On-Demand System with ShortCuts (ODS-SC). Similar to the DRS-ES, the ODS-SC aims to increase the efficiency of service during peak hours by allowing vehicles to take shortcuts between the city center and the terminal. Unlike the DRS-ES, the decisions are optimized based on passenger requests for the peak hours