Managing truck arrivals with time windows to alleviate gate congestion at container terminals

Abstract

Abstract Long truck queues at gates often limit the efficiency of a container terminal and generate serious air pollution. To reduce the gate congestion, this paper proposes a method called ‘vessel dependent time windows (VDTWs)' to control truck arrivals, which involves partitioning truck entries into groups and assigning different time windows to the groups. The proposed VDTWs method includes three steps: (1) predicting truck arrivals based on the time window assignment, (2) estimating the queue length of trucks, and (3) optimizing the arrangement of time windows to minimize the total cost in the system. A conventional Genetic Algorithm (GA), a multi-society GA, and a hybrid algorithm using GA and Simulated Annealing are used to solve the optimization problem. A case study based on a real container terminal in China is performed, which shows the VDTWs method can flatten the truck arrivals and reduce the gate congestion significantly.