The performance of a container terminal is typically evaluated using two main indicators: the vessel berthing time and the truck turnaround time. These two indicators are significantly influenced by the truck’s arrivals and departures to/from the container terminal. In the truck appointment scheduling problem, it is desired to designate a time slot for each truck to pick up/deliver a container from/to the container terminal while considering the objectives and constraints of the terminal and the trucking companies. Truck appointment systems are considered as a solution to control the truck arrivals and improve terminal efficiency. This paper presents a comprehensive review and analysis of the literature addressing the external truck appointment scheduling problem and presents possible directions for future research. After explaining the problem and its importance, the reviewed literature is classified based on three main categories: control and decision perspectives, modelling methodologies, and collaboration between stakeholders. Furthermore, the impact of implementing information and communication technologies on the external truck appointment scheduling problem is addressed. The paper covers the most recent publications and discusses their contributions. Besides, research gaps and future research directions are concluded.

Background: Scheduling the arrival of external trucks in container terminals is a critical operational decision that faces both terminal managers and trucking companies. This issue is crucial for both stakeholders since the random arrival of trucks causes congestion in the terminals and extended delays for the trucks. The objective of scheduling external truck appointments is not only to control the workload inside the terminal and the costs resulting from the excessive waiting times of trucks but also, to reduce the truck turnaround time. Methods: A binary programming model was proposed to minimize the waiting time cost, demurrage cost, and container delivery cost. Moreover, a sensitivity analysis was performed to compare various scenarios in terms of cost and to study to what extent the workload level is affected. The mathematical model was solved using Gurobi© 8.1.0 software. Results: 30 instances found in the literature were solved and evaluated in terms of the objective function value (i.e., cost) and truck turnaround time before and after controlling the workload inside the container terminal using the new proposed constraint. Conclusions: The obtained results showed a better distribution of the terminal workload, as well as a lower truck turnaround time that reduces the total cost.