Dynamic vessel schedule recovery strategy of liner shipping with uncertainties: An event-triggered model predictive control solution

Artikel i vetenskaplig tidskrift, 2024

Considering uncertain disturbances in the vessel schedule recovery problem (VSRP) of liner shipping, a schedule recovery model based on a receding horizon optimization mechanism is proposed. We build a hybrid automaton in mixed logical dynamical (MLD) approach and an event-triggered model predictive control (e-MPC) controller based on a dynamic strategy to perform online optimization and to handle with uncertainties. We compare the performances of the traditional static strategy, the single-speed management strategy, and the proposed dynamic strategy; the results of the experiments validate the effectiveness and superiority of the dynamic strategy. We further explore the impact of the magnitude of disturbance, stakeholder preferences, and collaborative agreements between liner companies and terminal operators through sensitivity analysis and finally derive recommendations for liner company operations from the analysis of the experimental results.