Print Email Facebook Twitter Data-driven preference-based routing and scheduling for activity-based freight transport modelling Title Data-driven preference-based routing and scheduling for activity-based freight transport modelling Author Nadi Najafabadi, A. (TU Delft Transport and Planning) Yorke-Smith, N. (TU Delft Algorithmics) Snelder, M. (TU Delft Transport and Planning; TNO) van Lint, J.W.C. (TU Delft Transport and Planning) Tavasszy, Lorant (TU Delft Transport and Planning) Date 2023 Abstract Understanding preferences and behaviours in road freight transport is valuable for planning and analysis. This paper proposes a data-driven vehicle routing and scheduling approach for use as a descriptive tool to study road freight transport activities. The model developed seeks to capture planners’ or drivers’ preferences in order to reproduce observed road freight activities. The model is based on a parametrized time-dependent vehicle routing problem whose parameters can be estimated from a set of observed planned tours. We propose a Bayesian optimization technique for parameter estimation of the model. Empirical results show that the model can fit real-world data accurately and synthesize tour flows close to reality. Subject Activity-based tour modellingBayesian optimizationData-driven routing and schedulingFreight transport modellingPreference-based vehicle routing To reference this document use: http://resolver.tudelft.nl/uuid:c806cda9-e049-4bb5-822e-52f602c58d74 DOI https://doi.org/10.1016/j.trc.2023.104413 ISSN 0968-090X Source Transportation Research. Part C: Emerging Technologies, 158 Part of collection Institutional Repository Document type journal article Rights © 2023 A. Nadi Najafabadi, N. Yorke-Smith, M. Snelder, J.W.C. van Lint, Lorant Tavasszy Files PDF 1_s2.0_S0968090X23004035_main.pdf 2.82 MB Close viewer /islandora/object/uuid:c806cda9-e049-4bb5-822e-52f602c58d74/datastream/OBJ/view