Post by TU Delft | Mechanical Engineering

Transport and logistics systems are more complex than they seem, with supply and demand constantly changing. Researchers at the faculty of Mechanical Engineering, Bilge Küçük Atasoy and Javier Durán Micco, develop advanced logistics models that combine optimisation, behavioural insights and machine learning. These models make it possible to adapt decisions dynamically, from routing and scheduling to network design, based on real time information and user behaviour. This approach improves the use of available capacity, reduces inefficiencies such as empty transport and supports more sustainable logistics systems. It also opens up new ways of organising transport in cities, for example by better coordinating different modes and using existing infrastructure more effectively. A strong example of how data driven models can reshape transport systems at scale. 🚢🚚 More Transport & Mobility research at ME 👉🏻 https://edu.nl/fqv89

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