Work

Large-Scale Package Deliveries With Unmanned Aerial Vehicles Using Collective Learning

Year: 2024

Type: article

Abstract: Unmanned aerial vehicles (UAVs) have significant practical advantages for delivering packages, and many logistics companies have begun deploying UAVs for commercial package deliveries. To deliver packages quickly and cost-effectively, the routes taken by UAVs from depots to customers must be optimized. We present an innovative, practical package-delivery model wherein multiple UAVs deliver multiple packages to customers, who are compensated for late deliveries. Further, we propose a novel methodology that combines a new plan-generation algorithm with a collective-learning heuristic to quickly determine cost-effective paths of UAVs, even for large-scale deliveries up to 10,000 customers. To demonstrate our methodology, we applied our highly flexible approach to a depot in Heathrow Airport, London. We show that our coordinated approach, in which the UAVs collectively determine their flight paths, leads to similar operational costs as those of the ant colony optimization technique and outperforms it for large-scale package deliveries.

Source: IEEE Intelligent Systems

DOI: 10.1109/mis.2024.3439535

Authors: Arun Narayanan, Evangelos Pournaras, Pedro H. J. Nardelli

Institutions: Lappeenranta-Lahti University of Technology, University of Leeds

Language: English

Topic: Vehicle Routing Optimization Methods

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $2,995