AbstractIn this paper, we propose a decision support tool to assist a local public transportation company in tackling service delays and small disruptions. We discuss different ways to assess and improve the regularity of the service, and we propose a simulation based optimization system that can be effectively used in a real-time environment taking into account both vehicle and driver shifts. In particular, we describe a tabu-search procedure for the online vehicle scheduling optimizing the regularity of the service and a column generation approach for the consequential crew re-scheduling minimizing the driver extra-time. As a case study, we analyze the management of urban surface lines of Azienda Trasporti Milanese (ATM) of Milan. In the last part of the paper we report a detailed analysis of the experimental phase showing the effectiveness of the proposed approach
Is data on this page outdated, violates copyrights or anything else? Report the problem now and we will take corresponding actions after reviewing your request.