Abstract
This paper focuses on the design of optimal feeder bus routes aimed at serving the commuting demand of suburban areas and increasing the ridership of a mass rapid transit system. The optimization problem presents a multi-objective nature. The transit operator is interested in maximizing the number of users served with the lowest vehicle kilometres travelled (i.e., maximizing profits), whereas passengers seek a high quality of service (i.e., minimizing travel times). An Ant Colony Optimization algorithm is here implemented into an agent-based modelling environment to find the optimal set of routes connecting the service area to multiple transfer stations. The potential demand at a feeder bus stop is estimated according to accessibility indicators, derived from GIS-based demographic data. The model is applied to the case study of Catania (a medium-sized city in Italy) to enhance the accessibility of urban railway stations via public transport. The proposed methodology can be used as a decision-making tool for transport operators and public administrations to understand how to design feeder bus routes to improve the accessibility of public transport.
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