Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/297207 
Year of Publication: 
2023
Citation: 
[Journal:] Logistics Research [ISSN:] 1865-0368 [Volume:] 16 [Issue:] 1 [Article No.:] 3 [Year:] 2023 [Pages:] 1-20
Publisher: 
Bundesvereinigung Logistik (BVL), Bremen
Abstract: 
Handling increasing volumes of parcel shipments in urban areas is one of the major challenges in city logistics. As the currently used conventional delivery by diesel vans is increasingly regarded critically by the public, alternative delivery concepts with cargo bikes, drones and robots have emerged in recent years. However, research studies that evaluate the benefits of such novel distribution systems usually investigate only one of them at a time. The contribution of this paper is to evaluate and compare the use of these alternative delivery options to identify efficient delivery systems for urban areas. To this end, a cost-oriented optimization model is presented in which, based on a two-echelon delivery system, parcel shipments are transported by comparably large vans from a depot outside of a city into the urban area to be distributed there by smaller vehicle types like cargo bikes or autonomous robots or drones. Thereby, the model enables both the integration of the first echelon vehicles into the final delivery, the transfer of parcels and smaller delivery vehicles within the urban area, the use of heterogeneous vehicles and the possibility to pickup further parcels during a tour. Computational studies are conducted for a real world city area to identify the benefits of using cargo bikes, robots, and drones in isolation or in combination under different parameter constellations such as population density of city segments, labor cost rates of the second echelon vehicles, and capacities of autonomous robots.
Subjects: 
City Logistics
Combined Delivery
Optimization Model
Cargo Bikes
Delivery Robots
Delivery Drones
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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