Abstract: In the container terminal operating systems, effectively berth quay scheduling is helpful to improve operational efficiency and customer satisfaction. For the simultaneous berth and quay crane scheduling problem with stochastic vessels arrival and working time, it considers the penalty time caused by the ship departure from the berth, and puts forward a method by adding a delay time to absorb the impact of uncertainty factors. ?In order to reflect the robustness of scheduling plan, this paper adds delay time in the objective function, and sets up a mixed integer programming model with the goal of minimizing the sum of the total time of vessels in port, the penalty time caused by the ship departure from the berth, customer satisfaction and delay time, and puts forward a improved Genetic Algorithm（GA） combined with since change GA and heuristic berthing to solve the model. By the analysis of examples, it is proved that the improved GA is effective in calculating the simultaneous berth and quay crane scheduling problem under stochastic environment.

Key words: continuous berth, stochastic, delay time, heuristic berthing, improved Genetic Algorithm（GA）

摘要： 在集装箱码头操作系统中，有效的泊位岸桥调度计划有助于提高码头的运营效率和客户满意度。针对船舶到港时间和装卸作业时间随机的泊位岸桥联合调度问题，综合考虑了连续泊位下船舶偏离偏好泊位产生的惩罚时间，并通过添加延缓时间的方法来吸收不确定性因素带来的影响。为了体现调度计划的鲁棒性，将延缓时间添加在目标函数中，建立了以船舶在港总时间、偏离偏好泊位的惩罚时间、客户满意度和延缓时间之和最小化为目标的混合整数规划模型，提出一种自改变遗传算法和启发式靠泊相结合的改进遗传算法对模型进行求解；通过算例分析，证明了提出的改进遗传算法在计算不确定环境下的泊位岸桥联合调度问题的有效性。

关键词: 连续泊位, 随机, 延缓时间, 启发式靠泊, 改进遗传算法