Modelling the Time-dependent VRP through Open Data
This work provides a straightforward and open-access method for logistics and urban planning to model and solve routing problems with traffic variability, though it is incremental as it builds on existing state-of-the-art techniques.
The paper tackles the vehicle routing problem with time-dependent travel times by developing an open data approach that uses online cartography services to create a multi-layer travel time matrix, which was applied to a medium-sized problem in Paris using an enhanced GRASP algorithm, achieving a solution that accounts for traffic variability.
This paper presents an open data approach to model and solve the vehicle routing problem with time-dependent travel times (TDVRP). The proposed model is based on a multi-layer matrix composed of travel times, replacing the traditional distance matrix. Online cartography services are queried in order to build this matrix. Travel times are obtained for every step in the time discretization. Thus, the model integrates the fact that the travel time between two points is modified during the time horizon. This model is applied to a medium-sized problem in the urban area of Paris using an enhanced Greedy Randomized Adaptive Search Procedure (GRASP). This work intends to build on the current state of the art by proposing a straightforward and open-access method to model and solve the VRP with traffic variability.