An adaptive large neighborhood search heuristic for the flying sidekick traveling salesman problem with multiple drops

• Published in: Expert systems with applications Vol. 205; p. 117647
• Main Authors: Windras Mara, Setyo Tri, Rifai, Achmad Pratama, Sopha, Bertha Maya
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01-11-2022
• Subjects: Adaptive large neighborhood search; Flying sidekick traveling salesman problem; Last-mile delivery; Logistics; Multi-visit; Truck-drone system; Adaptive large neighborhood search; Flying sidekick traveling salesman problem; Last-mile delivery; Truck-drone system; Multi-visit; Logistics
• ISSN: 0957-4174; 1873-6793
• DOI: 10.1016/j.eswa.2022.117647

•We discuss Flying Sidekick Traveling Salesman Problem (FSTSP) with multiple drops.•The drone can execute a short delivery trip to serve multiple customers.•We present a new mathematical formulation for this multi-drop FSTSP.•A new heuristic based on Adaptive Large Neighborhood Search (ALNS) is developed.
Drones are the latest trend in commercial logistics research, especially in the context of last-mile delivery. Combining a drone and a truck offers numerous distinctive capabilities that introduce new opportunities to enhance the performance of the last-mile delivery system even further. To deal with the challenges of routing optimization for the combined system, the present paper proposes a new mathematical formulation and a new heuristic approach based on Adaptive Large Neighborhood Search (ALNS) for the Flying Sidekick Traveling Salesman Problem (FSTSP) with multiple drops (multi-drop FSTSP). The effectiveness of the proposed approach was demonstrated in several test instances, some of which are based on a real case delivery problem in Indonesia. It appears that the proposed ALNS approach performs better than the state-of-the-art method adapted from the previous literature.