Deadline Date: 01 April 2026
Explosive growth in e-commerce and urbanization is straining conventional logistics networks and amplifying carbon footprints. Integrating evolutionary optimization, reinforcement learning (RL) and large-language-model (LLM) reasoning promises greener, more resilient and customer-centric "Smart Urban Logistics.
This Special Issue seeks cutting-edge research that designs, analyses and validates intelligent, explainable and sustainable logistics solutions by fusing evolutionary algorithms, RL and LLMs with IoT, 5G, digital twins and cloud–edge platforms. Submissions should tackle real-time routing, last-mile delivery, multi-agent collaboration, carbon-aware decision-support and disruption-resilient operations in urban and maritime contexts. Both theoretical advances and application case studies are welcome, including benchmarks, open datasets and reproducible frameworks.
1. Hybrid evolutionary–RL algorithms for dynamic vehicle routing and scheduling.
2. Multi-agent LLM-driven coordination in urban freight and port logistics.
3. Digital-twin and metaverse simulation for predictive logistics planning.
4. IoT-enabled carbon tracking and sustainability assessment.
5. Resilient logistics under disruption: uncertainty modelling and adaptive control.
6. Industry 5.0 human-in-the-loop decision support for last-mile delivery.
Explosive growth in e-commerce and urbanization is straining conventional logistics networks and amplifying carbon footprints. Integrating evolutionary optimization, reinforcement learning (RL) and large-language-model (LLM) reasoning promises greener, more resilient and customer-centric "Smart Urban Logistics.
Editorial board
