Highlights We develop a descriptive shipment-based algorithm for tour formation. The algorithm iteratively allocates shipments to tours using random utility models. A large Dutch shipment database is used to estimate explanatory variables. Commodity/location/vehicle attributes and logistical costs influence tour choices. Out-of-sample validation shows a close reproduction of observed tour statistics.
Abstract An increasing amount of research is dedicated to the consideration of tour formation in freight transportation demand models. While empirical tour formation models so far have been starting from limiting assumptions about the resulting trips, we develop a generalized shipment-based model. We formulate a random utility model embedded in an iterative algorithm to construct tours through the incremental allocation of shipments. It considers different objectives and constraints and acknowledges the difference between commodity, vehicle and location types. Parameters are estimated on a large and comprehensive shipment database. The model reproduces observed tour statistics well for the given set of shipments.
Descriptive modeling of freight tour formation: A shipment-based approach
2020-05-23
Article (Journal)
Electronic Resource
English
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