Abstract
Last-mile delivery (LMD) is an important aspect of contemporary logistics that directly affects operational cost, efficiency, and customer satisfaction. In this paper, we provide a review of the optimization techniques of LMD, focusing on Artificial Intelligence (AI) driven decision-making, IoT-supported real-time monitoring, and hybrid delivery networks. The combination of AI and IoT improves predictive analytics, dynamic routing, and fleet management, but scalability and regulatory issues are still major concerns. Hybrid frameworks that integrate drones or Unmanned Aerial Vehicles (UAVs), ground robots, and conventional vehicles reduce energy expenditure and increase delivery range, especially in urban contexts. Furthermore, sustainable logistics approaches, including electric vehicle fleets and shared delivery infrastructures, provide promise for minimizing environmental impact. However, economic viability, legal frameworks, and infrastructure readiness still influence the feasibility of large-scale adoption. This review offers a perspective on the changing patterns in LMD, calling for regulatory evolution, technological advancement, as well as interdisciplinary approaches toward cost-effective, durable, and environmentally friendly logistics systems.
| Original language | English |
|---|---|
| Article number | 158 |
| Journal | Drones |
| Volume | 9 |
| Issue number | 3 |
| DOIs | |
| State | Published - Mar 2025 |
Bibliographical note
Publisher Copyright:© 2025 by the authors.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 8 Decent Work and Economic Growth
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SDG 11 Sustainable Cities and Communities
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SDG 17 Partnerships for the Goals
Keywords
- drone
- last-mile delivery
- logistics
- optimization
- sustainability
ASJC Scopus subject areas
- Control and Systems Engineering
- Information Systems
- Aerospace Engineering
- Computer Science Applications
- Artificial Intelligence
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