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A matheuristic approach for the mobile parcel locker delivery system with delivery robots and drone resupply

Cheng, Chen, Demir, Emrah ORCID: https://orcid.org/0000-0002-4726-2556, Li, Wenke, Hu, Xisheng, Huang, Hainan and Li, Jian 2025. A matheuristic approach for the mobile parcel locker delivery system with delivery robots and drone resupply. Swarm and Evolutionary Computation 99 , 102182. 10.1016/j.swevo.2025.102182
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Abstract

Motivated by the rapid advancement of autonomous technologies in urban logistics, this research introduces a novel variant of vehicle routing problem with autonomous resources, including mobile parcel lockers (MPLs), delivery robots and drones. In this problem, customers choose between home delivery and self-pickup from lockers at designated parking areas. Robots are deployed from MPLs which are resupplied by drones as needed. We define this problem as the Mobile Parcel Locker Problem with Delivery Robot and Drone Resupply (MPLPDR-DR). To solve it, we formulate a mixed-integer linear programming (MILP) model and develop a matheuristic approach. This approach integrates a hybrid metaheuristic algorithm for optimizing the routing of MPLs and delivery robots, while a MILP model determines the optimal drone resupply decisions. The hybrid metaheuristic is built on the artificial bee colony framework and integrates a large neighborhood search procedure, a variable neighborhood descent procedure, and a mutation mechanism. The proposed approach also addresses synchronization challenges related to timing in parallel and sequential deliveries. Extensive experiments highlight the algorithm’s effectiveness on large set MPLPDR-DR instances, and the results offer valuable managerial insights.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Schools > Business (Including Economics)
Publisher: Elsevier
ISSN: 2210-6510
Date of First Compliant Deposit: 1 October 2025
Date of Acceptance: 30 September 2025
Last Modified: 15 Oct 2025 09:30
URI: https://orca.cardiff.ac.uk/id/eprint/181422

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