Data-driven preference-based routing and scheduling for activity-based freight transport modelling

Journal Article (2023)
Author(s)

A. Nadi Najafabadi (TU Delft - Transport and Planning)

N. Yorke-Smith (TU Delft - Algorithmics)

M. Snelder (TNO, TU Delft - Transport and Planning)

J.W.C. van Lint (TU Delft - Transport and Planning)

Lorant Tavasszy (TU Delft - Transport and Planning)

Transport and Planning
Copyright
© 2023 A. Nadi Najafabadi, N. Yorke-Smith, M. Snelder, J.W.C. van Lint, Lorant Tavasszy
DOI related publication
https://doi.org/10.1016/j.trc.2023.104413
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 A. Nadi Najafabadi, N. Yorke-Smith, M. Snelder, J.W.C. van Lint, Lorant Tavasszy
Transport and Planning
Volume number
158
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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.