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

• Main Authors: Mara, Setyo Tri Windras, Rifai, Achmad Pratama, Sopha, Bertha Maya
• Format: Article PeerReviewed
• Language: English
• Published: Elsevier 2022
• Subjects: Mechanical Engineering
• Online Access: https://repository.ugm.ac.id/278653/1/Mara-2_TK.pdf; https://repository.ugm.ac.id/278653/; https://www.sciencedirect.com/journal/expert-systems-with-applications; https://doi.org/10.1016/j.eswa.2022.117647
• Institution: Universitas Gadjah Mada

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.