Distributed model predictive control for cooperative synchromodal freight transport

Abstract

This paper investigates cooperative synchromodal freight transport planning among multiple intermodal freight transport operators in different and interconnected service networks. The cooperative planning is formulated as a cooperative model predictive container flow control problem, and solved with three Distributed Model Predictive Flow Control (DMPFC) approaches: the . parallel and . serial Augmented Lagrangian Relaxation (ALR) based DMPFC approaches, and the Alternating Direction Method of Multipliers (ADMM) based DMPFC approach. The simulation results show that the . serial ALR-based DMPFC approach requires the least iterations and information exchanges while the ADMM-based DMPFC approach takes the least amount of actual computation time.