The Quay Crane Scheduling Problem (QCSP) is one of the most important issues treated in container terminals because of its influence on the efficiency of port. The main goal behind this planning problem is to find the handling sequence of tasks at ship bays by a set of cranes assigned to a container vessel such that the time spent by vessels at berth is minimized. This study focused on optimizing quay crane scheduling in port container terminal to enhance their efficiency. So we provide a mixed-integer programming (MIP) model that takes into account non-crossing constraints, safety margin constraints and precedence constraints. To give a solution to this problem, we used a probabilistic technique for solving computational problems; this optimization methodology based on ant behaviors is named the Ant Colony Optimization (ACO).