Multi Objective Vehicle and Drone Routing Problem with Time Window

• Published in: 韓國컴퓨터情報學會論文誌 Vol. 24; no. 1; pp. 167 - 178
• Main Authors: Park, Tae Joon, Chung, Yerim
• Format: Journal Article
• Language: Korean
• Published: 한국컴퓨터정보학회 2019
• Subjects: Evolutionary Algorithm; Hybrid-Meta-Heuristics; Distribution Network; Multi-Objective Vehicle Routing Problem; Drone
• ISSN: 1598-849X; 2383-9945

In this paper, we study the multi-objectives vehicle and drone routing problem with time windows, MOVDRPTW for short, which is defined in an urban delivery network. We consider the dual modal delivery system consisting of drones and vehicles. Drones are used as a complement to the vehicle and operate in a point to point manner between the depot and the customer. Customers make various requests. They prefer to receive delivery services within the predetermined time range and some customers require fast delivery. The purpose of this paper is to investigate the effectiveness of the delivery strategy of using drones and vehicles together with a multi-objective measures. As experiment datasets, we use the instances generated based on actual courier delivery data. We propose a hybrid multi-objective evolutionary algorithm for solving MOVDRPTW. Our results confirm that the vehicle-drone mixed strategy has 30% cost advantage over vehicle only strategy.