UAV based coordinative pick-up and delivery scheduling: an application of ALNS algorithm

This study introduces a new variant of the pickup and delivery problem in on-demand delivery. Two types of vehicles (i.e. UAVs and crowdsourced riders) serve consumers of the on-demand platform. The goal of URCSP is to minimize the total operating cost of the platform’s two-vehicle fleets, delivery fresh-time and maximize the service quality at the same time. To address this problem, we develop a mixed integer programming model which is further solved by an Adaptive Large Neighborhood Search (ALNS) heuristic based on real data. Computational results show that the algorithm provides highquality solutions with reduced running time. We conclude that the collaboration delivery mechanism including both UAVs and riders can help instant delivery platforms reduce costs and increase efficiency.