Multiobjective Scheduling of Logistics UAVs Based on Variable Neighborhood Search

Abstract

This study focuses on the issue of logistics Unmanned Aerial Vehicle (UAV) distribution in urban environment and an automatic delivery system to support the delivery of packages. It can effectively integrate existing facilities and be easily deployed. There is a scheduling problem in this system with multiple UAVs and multiple flights. We manage to optimize the two objectives of customer satisfaction and total completion time. The scheduling problem is formulated to a Mixed Integer Linear Programming (MILP), and we propose a multiple objectives decision-making method. A special encoding method suitable for the small scale problem is presented and Variable Neighborhood Search (VNS) algorithm framework is used to generate the approximate optimal solution for this problem. In experiments, we calibrate the important parameter and analyze the robustness of the algorithm. The experimental results show that the proposed algorithms are efficient for this problem.