Optimization of two-echelon last-mile delivery via cargo tunnel and a delivery person

More and more people live in urban areas in general and in megacities, with 10 million inhabitants and more, in particular. One innovative instrument to reduce surface traffic and its negative impact on health, congestion, environment, and safety when supplying these urban inhabitants with goods is a cargo tunnel. Within the cargo tunnel concept, autonomous rail-bound, maglev, or automated guided vehicles deliver goods underground toward small inner-city hubs, from where the final leg toward customer homes can be executed with environmentally-friendly vehicles such as cargo bikes or electric vans. In addition to the huge investment costs for tunnel boring, this last-mile delivery option faces a challenging operational problem, which is the synchronization of goods arrivals at a capacity-restricted inner-city hub with the delivery tours. We formulate a basic two-echelon optimization problem that captures all main operational challenges of this synchronization task, derive suitable optimization procedures, and apply them in a computational study. The latter explores the interdependence between tunnel throughput, storage capacity at the hub, and vehicle capacity of the delivery person and their impact on delivery performance. An additional benchmark test with conventional truck-based deliveries shows that the reductions of carbon dioxide emissions promised by a cargo tunnel come for the price of excessive cargo bike traffic, especially if large urban regions are to be serviced from a micro hub.

Automated summary

More and more people are living in urban areas, particularly in megacities. To reduce the negative effects of surface traffic on health, congestion, environment, and safety, a cargo tunnel is proposed as an innovative solution for delivering goods to urban inhabitants. The concept involves autonomous rail-bound or maglev vehicles delivering goods underground to small inner-city hubs, from where environmentally-friendly vehicles can complete the final leg of delivery. However, there are operational challenges in synchronizing goods arrivals at the inner-city hubs with delivery tours. An optimization problem is formulated to address this issue and explore the impact of tunnel throughput, storage capacity at the hub, and vehicle capacity on delivery performance. A benchmark test shows that while a cargo tunnel reduces carbon dioxide emissions, it can lead to excessive cargo bike traffic in large urban regions.