In Container Terminals (CTs), many containers are daily delivered by a large number of External Trucks (ETs) which lead to several issues such as long waiting times at gates and yards, harmful emissions, and low productivity of the CTs. To resolve these issues, truck appointment systems are used to schedule appointments of ETs and achieve more balance in CTs’ workload. Most of the studies have focused on deterministic modelling of the ETs’ arrival process with considering yard operations or gate operations. Also, a little effort has been devoted to collaboration between trucking companies and CTs when scheduling ETs’ appointments. Unlike previous studies, this paper presents a simulation-based optimization approach to collaboratively schedule ETs’ appointments with considering yard and gate operations as well as their stochastic natures. The proposed approach integrates a simulation model with an MIP model with objective of minimizing turnaround times of ETs and inconveniences resulting from shifting the arrivals of ETs away from their preferred arrival times. The proposed approach is validated against an approach from literature. In addition, its performance is investigated by solving artificial instances inspired by real data. A framework for implementing the proposed system in the IoT-based container terminals is also developed.