Innovative sensors enable capturing large amounts of data about freight flows and are more and more applied in practice. The project particularly focuses on:
Use sensory data to better estimate temperature changes during transport operations Incorporate insights from sensory data in deterministic models and algorithms for integrated sustainable decision-making on consolidating products into trucks, designing distribution routes and on operating the cooling equipment for fresh products. Exploring sensory data to define data-driven stochastic/robust models to support dynamic decision making Decide on the vehicle fleet mixt for sustainable and cost-efficient transport plans Evaluate the benefits of the data-driven stochastic/robust decision models using real-life data