A multi-objective approach for the integrated planning of drone and robot assisted truck operations in last-mile delivery

Mokhtari-Moghadam, A, Salhi, A, Yang, X, Nguyen, TT and Pourhejazy, P (2025) A multi-objective approach for the integrated planning of drone and robot assisted truck operations in last-mile delivery. Expert Systems with Applications, 269. ISSN 0957-4174

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Abstract

Supply chains are experiencing a major transition driven by changing customer expectations, environmental concerns, and technological development. Considering the surge in e-commerce since the pandemic, the path forward for affordable, responsive supply chains is autonomous last-mile delivery. Drone and robot technologies complement the last-mile delivery's operational requirements and hence should be incorporated to assist truck deliveries. This study develops a bi-objective optimization framework for the integrated planning of Drone-And-Robot-assisted Truck (DART) delivery operations to minimize total delivery cost and maximize customer satisfaction considering a soft time window. Three models, including DART, drone-, and robot-assisted trucks are compared considering different operational situations. The results show that the DART delivery mode outperforms with an increase in the number of demand points. DART is particularly preferred when there is a moderate combination of high-density and distant demand points in last-mile delivery. Numerical experiments confirmed that the robot-assisted delivery model brings about cost-effectiveness in heavily populated areas. On the other hand, the drone-assisted truck model stands out in situations where there is a small number of demand points with high dispersity.

Item Type:	Article
Uncontrolled Keywords:	3509 Transportation, Logistics and Supply Chains; 46 Information and Computing Sciences; 40 Engineering; 35 Commerce, Management, Tourism and Services; 01 Mathematical Sciences; 08 Information and Computing Sciences; 09 Engineering; Artificial Intelligence & Image Processing
Subjects:	T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	Engineering
Publisher:	Elsevier
Date of acceptance:	4 January 2025
Date of first compliant Open Access:	27 May 2025
Date Deposited:	27 May 2025 15:18
Last Modified:	27 May 2025 15:30
DOI or ID number:	10.1016/j.eswa.2025.126434
URI:	https://researchonline.ljmu.ac.uk/id/eprint/26431

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