Given the rising growth in containerized trade, Container Terminals (CTs) are facing truck congestion at the gate and yard. Truck congestion problems not only result in long queues of trucks at the terminal gates and yards but also leads to long turn times of trucks and environmentally harmful emissions. As a result, many terminals are seeking to set strategies and develop new approaches to reduce the congestions in various terminal areas. In this paper, we tackle the truck congestion problem with a new dynamic and collaborative truck appointment system. The collaboration provides shared decision making among the trucking companies and the CT management, while the dynamic features of the proposed system enable both stakeholders to cope with the dynamic nature of the truck scheduling problem. The new Dynamic Collaboration Truck Appointment System (DCTAS) is developed using an integrated simulation-optimization approach. The proposed approach integrates an MIP model with a discrete event simulation model. Results show that the proposed DCTAS could reduce the terminal congestions and flatten the workload peaks in the terminal.