为研究岸电船舶优先靠泊和分时电价政策对船舶泊位和岸桥调度的影响，构建一个以最小化船舶总成本和最小化碳排放量为目标的泊位岸桥联合动态调度非线性混合整数规划模型。通过双种群协同进化和自适应交叉、变异算子改进基于非支配排序的遗传算法（non-dominated sorting genetic algorithm Ⅱ, NSGA-Ⅱ）算法进行求解，并验证算法有效性。结果表明：改进NSGA-Ⅱ的求解效果优于NSGA-Ⅱ；分时电价下，岸电船舶靠泊优先政策能有效降低岸电船舶成本，提高非岸电船舶改造和使用岸电的积极性；峰谷电价差越大则调度方案的岸电船舶成本越大、非岸电船舶成本越小、所有船舶的碳排放量越小，同时更多岸电船舶为了减少高峰用电而选择不优先靠泊。研究结果可为在岸电船舶优先靠泊和分时电价政策下制定合理的调度方案提供科学依据。

In order to study the impacts of berthing priority of shore power ships and time-of-use price on scheduling of berths and quay cranes. A nonlinear mixed-integer planning model was constructed for the joint dynamic scheduling of berths and quay cranes with the goal of minimizing the total cost of ships and carbon emissions. The non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ) was improved by two-population co-evolution and the adaptive operators of crossover and mutation to solve the model, and the effectiveness of the improved algorithm was verified. The results show that the solution effect of improved NSGA-Ⅱ is better than that of NSGA-Ⅱ. Under time-of-use price, the berthing priority for shore power ships can effectively reduce the cost of shore power ships and improve the enthusiasm of no shore power ships to retrofit and use shore power. The bigger the gap between the electricity price of peak and low period is the higher the cost of shore power ships and the lower the carbon emission and the cost of no shore power ships. More shore power ships do not give priority to berthing to avoid the electricity price of peak period. The results of the study can provide a scientific basis for the development of reasonable scheduling scheme under the policy of berthing priority and time-of-use price for shore power ships.