Collaborative last mile delivery: A two-echelon vehicle routing model with collaboration points

Collaboration is key to addressing operational efficiencies, and in the context of last mile delivery, operational inefficiencies arising from empty trips, low load factor, and long dwell times require collaboration amongst multiple logistics service providers (LSPs). However, existing studies in the last mile delivery adopting collaboration as a means of sharing strategic infrastructure assets, such as distribution centers (DCs), satellites, and driving vehicles, might not be seen as favorable for logistics service providers due to ownership disputes and loss of control over assets. To address this limitation, a new routing method for addressing operational efficiencies in last mile delivery has been proposed in this study, allowing for collaboration across multiple logistics service providers without sharing strategic assets. We have formulated a two-echelon vehicle routing problem with collaboration Points (2E-VRP-CP) where the exchange of goods happens between second-echelon vehicles belonging to different logistics service providers. The method uses a mixed-integer linear programming model (MILP) that minimizes the total distribution cost and has been tested on randomly generated instances. Results suggest that the proposed collaborative approach of exchanging goods between second-echelon vehicles belonging to different logistics service providers can reduce costs by up to 10% relative to the non-collaborative approach and up to 9% compared to the existing collaborative approach that shares strategic assets. A four-phase heuristic algorithm has also been developed to tackle computationally expensive larger instances, which can obtain cost savings of up to 15% compared to a non-collaborative approach. Future work will involve developing a profit-allocation mechanism and will consider additional constraints to make the model more realistic in addressing a real-world problem. Overall, this model can help fleet managers achieve efficient fulfillment in last mile delivery, while the proposed heuristics can enable stakeholders to scale their solutions to real-world scenarios.