ORDER ALLOCATION AND VEHICLE ROUTING PROBLEMS WITH CROWDSOURCED AND PROFESSIONAL COURIERS

Abstract

<p>This study investigates the order allocation and vehicle routing problems of an integrated logistics platform with crowdsourced and professional couriers. Specifically, we consider the Pickup and Delivery Problem with Time Windows, Transshipment, and Consolidation (CS-PDPTWTC), where trucks, professional couriers, and crowdsourced carriers (crowd-carriers) collaborate to serve all pickup and delivery requests from intercity and intracity. Trucks consolidate parcels among service points and the distribution center. Professional couriers depart from service points and handle pickup and delivery tasks inside their service region. Meanwhile, crowd-carriers can perform delivery tasks using parcel lockers as transshipment points. In other words, professional couriers can deposit the parcels in lockers for temporary storage, and then crowd-carriers can collect the parcels from lockers and deliver to the final destination. The objective is to minimize the total delivery cost while satisfying all demands by optimizing order allocation and vehicle routing. The CS-PDPTWTC problem is formulated as a Mixed Integer Linear Programming (MILP) model. As the CS-PDPTWTC is NP-hard, we develop an Adaptive Large Neighborhood Search (ALNS) algorithm that significantly improves solving efficiency. Numerical results across different scenarios show that integrating crowdshipping into pickup and delivery services can reduce operational costs, offering substantial economic benefits. Sensitivity analysis further indicates that the operator can reduce the logistics cost by attracting more potential crowd-carriers, reducing their compensation rate, and increasing the number of service points within a certain range.<br></p>