Multi-Objective Multi-Drone Collaborative Routing Problem With Heterogeneous Delivery and Pickup Service

With the development of e-commerce, the types of logistics services have become diverse. In response to the logistics requirements in urban environments, this paper introduces a logistics system that multiple drones and smart parcel lockers (SPLs) collaborate to provide package pickup, delivery and intra-city on-demand delivery services for customers. Different from pickup and delivery services, the intra-city on-demand delivery services need drones to pick up a package from a customer and deliver it to another customer. The multi-drone collaborative routing problem is crucial to find a reasonable tour over customers with flexible time-window. A multi-objective mixed-integer programming model is formulated to describe the proposed problem with simultaneously minimizing transportation costs and maximizing customer satisfaction. The model integrates dynamic energy consumption, soft time-windows, and task precedence constraints arising from the single unit capacity of drones. To tackle this problem, an adaptive-large-neighborhood-search based multi-objective algorithm (ALNSMO) is devised. CPLEX is used to verify the accuracy of the model and the quality of the proposed algorithm. Meanwhile, numerous experiments and analyses are conducted to demonstrate the superiority and practicability of the proposed mode and ALNSMO.