An algorithmic framework for computing shortest routes in urban multimodal networks with different criteria

In this paper we deal with shortest paths in the context of urban passenger mobility. In particular, we present a novel shortest path algorithm on multimodal networks, where the objective function may consist of different components, such as monetary cost, time and discomfort paid by users when changing modality. The key feature of the proposed algorithm is that it focuses on the modal change nodes and forces as much as possible routings through those nodes that could be profitably selected as commuting points. Since modal change nodes play a relevant role in the choice of the route, we evaluate the performance of such nodes with the aim of increasing their attractiveness, thus minimizing the generalized cost of the multimodal routes. The underlying model fits in the class of multi – weighted graph approach, where here weights are associated with both arcs and nodes of the multimodal digraph. Results of a computational experimentation aimed at validating the proposed algorithm with different sized multimodal networks are reported, together with a case study related to the city of Genoa, Italy. Finally, a sensitivity analysis on the arc weight is performed, and related preliminary computational results are given.