A bi-objective optimisation model for the drone scheduling problem in island delivery

Ying Yang, Jiaxin Liu and Shuaian Wang

International Journal of Production Research, 2025, vol. 63, issue 19, 7174-7195

Abstract: Drone-assisted parcel delivery to remote islands is increasingly replacing traditional methods, offering improved efficiency and enhanced service reliability. This paper addresses the drone scheduling problem in island delivery (DSP-ID) by optimising drone delivery routes. In particular, we first introduce a bi-objective mixed-integer linear programming model that concurrently optimises delivery time and energy consumption. To address the model, both a heuristic non-dominated sorting genetic algorithm II (NSGA-II) and an exact augmented ε-constraint method are developed. The efficacy and robustness of the proposed model and algorithms are evaluated through experiments across various scales. Results indicate that both algorithms yield high-quality solutions for DSP-ID in small-scale scenarios. However, as the problem size expands, the performance of the augmented ε-constraint method wanes under time constraints, whereas the NSGA-II consistently delivers high-quality solutions. Additionally, we provide decision-makers with actionable insights for selecting the most effective drone delivery routes.

Date: 2025
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DOI: 10.1080/00207543.2025.2496965

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