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A hybrid variable neighborhood search heuristic for the sustainable time-dependent truck-drone routing problem with rendezvous locations

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Abstract

As an innovative approach to city logistics, the truck and drone delivery systems piqued the interest of academia and various companies in recent years, which takes advantage of both trucks’ large capacity and drones’ high speed. In congested city areas, dense traffic significantly impacts delivery time and all three sustainable dimensions (economic, environmental, and social) of delivery systems. For this reason, we focused on the sustainable time-dependent truck and drone routing problem with rendezvous locations. This work processes with a hybrid variable neighborhood search algorithm. We carried out numerous computational experiments to evaluate the performance of the proposed algorithm, and the results show its efficiency. Finally, by performing a detailed sensitivity analysis, the result highlights that the proposed model can reduce the completion time, operational costs, truck emissions, and social penalties in comparison to the flying sidekick traveling salesman model.

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The data that support the findings of this study are available from the corresponding author, upon reasonable request.

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Acknowledgements

The authors should highly acknowledge and thank the kind support of (i) three anonymous reviewers as well as the editor-in-chief for their insightful comments, and (ii) Dr. Mehdi Karimi-Nasab for numerous guidance on the issues related to the design and analysis of the optimization algorithms

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  1. Department of Industrial Engineering, Iran University of Science and Technology, Narmak, Tehran, 16844, Iran

    Ebrahim Teimoury & Reza Rashid

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  1. Ebrahim Teimoury
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Correspondence to Ebrahim Teimoury.

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Teimoury, E., Rashid, R. A hybrid variable neighborhood search heuristic for the sustainable time-dependent truck-drone routing problem with rendezvous locations. J Heuristics 30, 1–41 (2024). https://doi.org/10.1007/s10732-023-09520-z

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