Cross-system control of transport and intralogistics for sustainable distribution in the physical Internet
Original Language Title: Systemübergreifende Steuerung von Transport- und Intralogistik zur nachhaltigen Distribution im Physical Internet
The research project StandPI enables the efficient usage of Crowdsourcing Delivery for the loading industry. Therefore, internal and external system parameters will be continuously monitored, and these real-time data will be further processed by a machine learning algorithm. By the means of this algorithm, the matching of the loader’s product supply and the dynamic available transportation capacities in respect to Crowdsourcing Delivery will be optimized.
Eventually, in contrast to the nowadays commonly used sequentially controlling and optimization of the transportation and inner logistics systems, the aim of this research project is a self-learning controlling, which acts at the interface of these system, concerning a cross system optimization. Hence, consistent exploitation of the remaining capacities of vehicles en route will significantly contribute to economical, ecological and social sustainability concerning physical distribution.