From synthetic population to parcel demand: A modeling pipeline and case study for last-mile deliveries in Lyon

International audienceThe paper describes an open and fully replicable pipeline to assess the performance of parcel delivery systems. Starting with publicly available data in France, a range of open source tools is used to create a synthetic population of the region from which its parcel delivery demand is derived. Using JSprit for solving the resulting Vehicle Routing Problem and simulating vehicle movements, a test case for automated delivery robots in the Confluence neighborhood of Lyon is set up and analyzed

From synthetic population to parcel demand: A modeling pipeline and case study for last-mile deliveries in Lyon

International audienceThe paper describes an open and fully replicable pipeline to assess the performance of parcel delivery systems. Starting with publicly available data in France, a range of open source tools is used to create a synthetic population of the region from which its parcel delivery demand is derived. Using JSprit for solving the resulting Vehicle Routing Problem and simulating vehicle movements, a test case for automated delivery robots in the Confluence neighborhood of Lyon is set up and analyzed

Modeling the ecological and economic footprint of last-mile parcel deliveries using open data: A case study for Lyon

International audienceThe amount of parcels delivered in the urban space is steadily increasing and is often expected to double by 2030. At the same time rising energy prices and policies towards sustainable development affect the business models and distribution schemes in the sector. The present study uses open data to approximate today’s parcel volumes for the specific case of Lyon and estimated how those parcels are delivered in terms of used vehicles, covered distances and ecological impacts. The first part describes our data collection process which hypothesizes market shares and cost structures of the parcel operators. In the second part, we solve Heterogeneous Vehicle Routing Problems to uncover the likely distribution schemes. This way, the study provides rough estimates on the total daily emissions and energy used for parcel deliveries outlined pathways for future modeling efforts and data collection

Control-based integration of rejection rates into endogenous demand ride-pooling simulations

International audienceThe potential of Mobility-on-Demand systems has frequently been studied in the literature, often in combination with dynamic demand models that respond to the obtained service levels. However, the endogenous demand usually does not respond to generated rejection rates. The paper discusses potential ways of integrating this dimension into a behavioral demand model. A linear control-based approach is proposed that penalizes choices for the on-demand service until a maximum desired rejection rate is obtained. The practical value of the method is demonstrated on a large-scale agent-based transport simulation and pathways for future improvements are provided

Towards Reproducible Simulations of the Grand Paris Express and On-Demand Feeder Services

International audienc

Towards Reproducible Simulations of the Grand Paris Express and On-Demand Feeder Services

International audienc

Towards Reproducible Simulations of the Grand Paris Express and On-Demand Feeder Services

International audienc

Implementing reinforcement learning for on-demand vehicle rebalancing in MATSim

International audienc

ADAPTING JSPRIT FOR THE ELECTRIC VEHICLE ROUTING PROBLEM WITH RECHARGING: IMPLEMENTATION AND BENCHMARK

International audienceThis article presents our adaptation of the Ruin-and-Recreate (R&R) algorithm to solve the electric vehicle routing problem with time windows and multiple trips. We implement this adaptation in JSprit, an open-source vehicle routing problem solver. We showcase the framework for a case study in Lyon, France. In the case study, we assess the efficiency impact of adding charging constraints to a simulation of a fleet of autonomous delivery robots. The framework is tested on benchmark instances and compared with results from literature