Mobility as a Service (MaaS) platforms allow users to plan, book and pay for trips that may involve a combination of multiple modes, including public transport (PT), demand-responsive shared taxis (DRT), bikesharing (BS) and walking. This project focuses on the design and optimization of such a hybrid mobility system. The design involves a number of strategic/tactical decisions (PT lines and frequencies, location and size of the BS stations, DRT fleet size) that are interdependent. The methodological challenge of these design decisions is to predict or analyse their impact on the operational costs and the service level upon implementation. To address this challenge, methodologies from Operations Research and Data Science will be applied.
Specifically, the goal of this project is to develop mathematical models and heuristic solution algorithms to solve the underlying (combinatorial) optimization problems when operating a hybrid urban mobility system. In addition, these algorithms are to be integrated in an optimization approach for taking strategic/tactical design decisions on such systems.
Candidates should have a strong background in operations research. Applying is only possible via the university's online portal (see https://www.uhasselt.be/en/about-hasselt-university/working-at-hasselt-university/vacancies/detail/2625-phd-student-urban-mobility).