Publication Type

Journal Article

Version

acceptedVersion

Publication Date

6-2025

Abstract

In the on-demand problem domain, actual demand frequently deviates from the expected demand. This paper intricately delves into the exploration of on-demand heterogeneous multi-drone routing problem (ODHDRP), in which a transport drone carries multiple terminal drones to subregions in the first echelon, and the terminal drones deliver parcels during a flight trip to customers with demands in subregions to maintain economies of scale in the second echelon. We formulate the customer demands using a normal distribution, and exploit a reliability model of customer demands with chance constraints. To solve the ODHDRP efficiently, we propose a hybrid iterative optimisation heuristic (HIOH) approach. Firstly, a clustering algorithm considering the drone's payload is designed to divide the customer-region into several subregions. Subsequently, the dynamic programming algorithm is introduced to generate the initial route to each subregion. Secondly, an iterative optimisation algorithm with heuristic operators and reliability-based strategies is designed to handle the chance constraints and optimise the routes. The experiments substantiate the superior performance of the proposed method in contrast to baseline algorithms. Moreover, the sensitivity of key factors in the proposed model is analysed and several managerial insights are derived.

Keywords

Two-echelon routing, heterogeneous drones, on-demand, heuristic algorithm, iterative optimisation algorithm

Discipline

Artificial Intelligence and Robotics | Operations Research, Systems Engineering and Industrial Engineering

Research Areas

Intelligent Systems and Optimization

Areas of Excellence

Digital transformation

Publication

International Journal of Production Research

First Page

1

Last Page

31

ISSN

0020-7543

Identifier

10.1080/00207543.2025.2512445

Publisher

Taylor and Francis Group

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1080/00207543.2025.2512445

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