The joint optimization of truck-drone routes for last-mile delivery

This article proposes a joint allocation problem between truck and drone. On the basis of considering the constraints of drone battery capacity and load capacity, a mixed integer programming model for collaborative delivery between drones and vehicles was constructed to minimize the total delivery cost. In order to effectively solve the coordinated distribution path planning problem of a single drone and a single aircraft, chaotic mapping is applied to the initial population, adaptive population ratios are used, and a spiral search strategy is adopted to improve the sparrow search algorithm. Several local search strategies have been proposed. Finally, numerical experiments verified its effectiveness and compared the proposed model with traditional travel salesman problem models, highlighting its advantages.

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Publication Details

Published
2025-03-21
DOI
https://doi.org/10.1109/iscait64916.2025.11010317
Primary Topic
Transportation and Mobility Innovations
Type
article
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article

The joint optimization of truck-drone routes for last-mile delivery

Lei Zhou, Yuhao Li, Chunxiao Li
Transportation and Mobility Innovations
article

The joint optimization of truck-drone routes for last-mile delivery

Lei Zhou, Yuhao Li, Chunxiao Li
article en

Abstract

This article proposes a joint allocation problem between truck and drone. On the basis of considering the constraints of drone battery capacity and load capacity, a mixed integer programming model for collaborative delivery between drones and vehicles was constructed to minimize the total delivery cost. In order to effectively solve the coordinated distribution path planning problem of a single drone and a single aircraft, chaotic mapping is applied to the initial population, adaptive population ratios are used, and a spiral search strategy is adopted to improve the sparrow search algorithm. Several local search strategies have been proposed. Finally, numerical experiments verified its effectiveness and compared the proposed model with traditional travel salesman problem models, highlighting its advantages.

Northeastern University (CN)
Openalex Percentile: Top 88%
Transportation and Mobility Innovations
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