Abstract: On the scheduling optimization of the yard equipment, more studied the combined dispatching of the inner container trucks and yard cranes under deterministic conditions, and less considered the random arrival time of the outer container trucks. The uncertain factors including the speed of the inner container trucks, the speed and the operation time of the yard cranes are considered. And according to the effect of the random arrival time of the outer container trucks on the scheduling operation of the inner container trucks, the optimization model considering the uncertain factors of the integrated scheduling of the yard equipment is established. The objective is to minimize the operation time of the yard equipment considering the random arrival time of the outer container trucks. So the particle swarm optimization algorithm is designed to settle the model, and the optimized results of the uncertain model are compared with that of the deterministic model. The numerical experiments and results represent that the model and the algorithm truly and effectively reflect the effect of the uncertain conditions on the operation of the yard equipment.

Key words: uncertain factors, integrated scheduling, yard equipment, outer container trucks

摘要： 集装箱码头堆场设备调度优化中，对确定条件下的内集卡和场桥的联合调度研究较多，且没有考虑外集卡的随机到达情况。考虑内集卡和场桥作业过程中的不确定性因素，包括：内集卡行驶速度，场桥行走速度和作业时间，并考虑外集卡随机到达堆场对于内集卡调度作业的影响，构建了不确定因素条件下的堆场设备集成调度优化模型，其优化目标是在考虑外集卡随机到达的情况下，最优化堆场设备的作业时间。设计了求解模型的粒子群算法，并比较了一般确定性模型和考虑不确定因素优化模型的结果。算例结果表明，所建立的模型和算法能有效真实地反映不确定因素对集装箱码头堆场设备作业的影响。

关键词: 不确定因素, 集成调度, 堆场设备, 外集卡