An adaptive large neighborhood search heuristic for the flying sidekick traveling salesman problem with multiple drops
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 wi...
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| Main Authors: | , , |
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| Format: | Article PeerReviewed |
| Language: | English |
| Published: |
Elsevier
2022
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| Subjects: | |
| 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 |
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| Institution: | Universitas Gadjah Mada |
| Language: | English |
| Summary: | 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. |
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