Container terminals play a significant role as representative logistics facilities for contemporary trades by handling outbound, inbound, and transshipment containers to and from the sea (shipping liners) and the hinterland (consignees). Capacity planning is a fundamental decision process when constructing, expanding, or renovating a container terminal to meet the demand, and the outcome of this planning is typically represented in terms of configurations of resources (e.g., the numbers of quay cranes, yard cranes, and vehicles) which enables the container flows to satisfy a high service level for vessels (e.g., berth-on-arrivals). This study presents a decision-making process which optimizes the capacity planning of large-scale container terminals. Advanced simulation-based optimization algorithms, such as MO-MO2TOS, MOCBA, and MO-COMPASS, were employed to formulate and solve the large-scale multi-objective problem optimally with multi-fidelity simulation models. Various simulation results were compared with one another in terms of the capacities over different resource configurations so as to understand the effect of various parameter settings on optimal capacity across the algorithms.