A Review of Hybrid Optimization Approaches for Eco-Friendly Vehicle Routing in Smart Cities

DOI

10.2991/978-94-6463-787-8_16How to use a DOI?

Keywords

Hybrid Optimization; Eco-Friendly Vehicle Routing; Smart Cities; Metaheuristic Algorithms; Multi-Objective Optimization; CO2 Emissions Reduction

Abstract

The rising demand for sustainable urban transportation has led to the growth of Eco-Friendly Vehicle Routing Problems, which aim to minimize environmental impacts while optimizing routing decisions. In smart cities, the integration of hybrid optimization techniques has recognized to be a promising solution to address the complex nature of vehicle routing, where multiple objectives, such as minimizing fuel consumption, energy use, and emissions, must be balanced with real-time constraints like traffic and weather conditions. This paper reviews hybrid optimization approaches for EVRP, focusing on the amalgamation of metaheuristic algorithms (e.g., GA, PSO, ACO) with ML techniques, like reinforcement learning and deep learning. These hybrid techniques enhance the flexibility and adaptability of vehicle routing systems, making them fit for the dynamic and evolving environment of smart cities. Also, the paper explores recent trends, including the use of real-time data from IoT sensors and the challenges posed by the scalability of these methods in large urban areas. While noteworthy improvements have been made, several research gaps remain, particularly in improving the scalability of hybrid algorithms, incorporating multi-modal transportation systems, and addressing the integration of emerging technologies like autonomous vehicles. Forthcoming research is central to enhance the effectiveness and sustainability of smart city transportation systems.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Amrita Prakash
AU  - Md. Amir Khusru Akhtar
PY  - 2025
DA  - 2025/07/17
TI  - A Review of Hybrid Optimization Approaches for Eco-Friendly Vehicle Routing in Smart Cities
BT  - Proceedings of the Recent Advances in Artificial Intelligence for Sustainable Development (RAISD 2025)
PB  - Atlantis Press
SP  - 177
EP  - 189
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-787-8_16
DO  - 10.2991/978-94-6463-787-8_16
ID  - Prakash2025
ER  -