An agent-based evolutionary approach for the user-oriented optimization of complex public transit systems

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The main goal of this project is to develop a methodology for a user-oriented optimization of public transport systems. The proposed approach will be integrated into an open source multi-agent simulation framework, where the interactions of public transport operators and users are simulated microscopically. The simulation-based optimization will account for the users' reactions, such as mode choice, route choice and departure time choice. For a given schedule-based public transit system, the model will be able to suggest improvements of transit routes, headways, service periods and pricing. As optimization objective, operator revenues and costs as well as user benefits will be considered. The methodology is based on the survival of the fittest principle found in competitive paratransit systems in the developing world. Therefore, it can additionally be used to construct a paratransit schedule when none is available for paratransit modeling of a region. In order demonstrate the real world applicability, the proposed optimization approach is applied to twolarge scale scenarios: Berlin as a study area where existing formal transit is to be improved; and a study area in South Africa with existing paratransit structures.