In this paper, we concern with the utilization and improvement of quantum-behavior heuristic algorithm for scheduling optimization problems. In order to solve a large-scale integral optimization problem with multiple extrema, a modified quantum-behavior genetic algorithm with strong global searching ability is developed with the following measures, including (i) a dynamic quantum rotation gate mechanism to improve the tendency of convergence, (ii) a criteria of annealing operation to improve global search ability, and (iii) a storage space and reconstruction operation for updating population. Meanwhile, a mathematical model of scheduling problem in container terminals is proposed named berth allocation, quay crane assignment and scheduling problem. At last, several experimental studies of scheduling optimization problems are taken in the experiment section, which verifies the effectiveness and the superiority of the modified algorithm.