In recent literature, it is indicated that freight transportation via trucks is still insufficient in terms of efficiency and sustainability. Reasons for such inefficiency are poor utilization of capacities (drivers, trucks, containers etc.), high shares of empty mileage, as well as lacking flexibility when responding to an increasing market volatility. It is assumed that future transport systems will have to deal with higher urgencies and with smaller lot sizes. In course of this, the assignment of transport orders will be characterized by increasing spontaneity and an uncertain planning environment for logistics service providers.
Thus, the objective of this paper is to present a conceptual model that combines a dynamical price prediction model and an approach for the dynamical assignment of freight flows through a network of hubs. Due to a constantly changing environment (e.g. demands, capacities, and/or prices), freight assignment will be updated continuously. As a result, the operational freight flow will evolve over time and choose the most cost-efficient route through the network by dynamically bundling and unbundling itself.
After a brief introduction on recent Physical Internet (PI) research, this paper will give a description of the proposed model, for a continuous and dynamic freight flow assignment. Eventually, we will discuss the results and conclude with the implications on our research.