Order allocation and vehicle routing with collaborative pickup and delivery by crowdsourced and contracted couriers in a two-echelon urban logistics system

This study investigates the order allocation and vehicle routing problems for an integrated logistics system that employs both crowdsourced and contracted couriers. Leveraging uncontracted travelers from the crowd, referred to as crowdsourced couriers, crowdshipping can provide flexible and cost-effective delivery service. However, this also introduces unique challenges, stemming from the limited delivery ranges of crowdsourced couriers constrained by their personal travel purposes, and reliability concerns due to the absence of formal labor contracts. Moreover, fulfilling both intracity and intercity pickup and delivery tasks mandates the incorporation of consolidation and transshipment strategies. To address these complexities, the paper presents a pickup and delivery problem with crowdshipping, transshipment, and consolidation (PDPCTC) model that jointly coordinates crowdsourced and contracted couriers in a two-echelon urban logistics system to fulfill demand across intracity and intercity. The study formulates the PDPCTC as a Mixed Integer Linear Programming (MILP) model to optimize order allocation and routing with the objective of minimizing the total delivery cost across the network. For scalability of our model in real-world scenarios, an Adaptive Large Neighborhood Search (ALNS) algorithm is developed. Numerical results across various simulated and real-world scenarios demonstrate that integrating crowdshipping into pickup and delivery services can significantly reduce operational costs, yielding considerable economic benefits. Sensitivity analysis further suggests that logistics costs can be reduced by attracting more potential crowdsourced couriers, lowering their compensation rate, and increasing the number of service points within a certain limit.