港口陆侧的集装箱集疏运系统是整个港口物流系统的重要组成部分。甩挂运输是一种先进的集疏运组织方式，当拖车拖运集装箱到达顾客处时，挂车和集装箱可以被甩在顾客处进行装卸货，而拖头可以直接去服务另一个顾客，待甩下的集装箱装卸货作业完成后可由其它拖头拖走。该模式下，顾客处的装卸货时间要求对拖车调度策略的生成影响很大。然而，按照确定的装卸货时间生成的调度策略在执行时往往会因为装卸货时间的不确定性而出现偏差，更甚者不可执行。本课题拟通过鲁棒优化的方法来求解不确定装卸货时间下的集装箱甩挂运输问题。具体来讲，本课题在前期对确定性甩挂运输问题的研究基础上，考虑不同的应用场景，在基于标称值、连续区间范围、离散情景和随机分布四种不确定装卸货时间类型下，分别建立对应的鲁棒优化模型，设计有效算法，求解满足一定目标准则的鲁棒最优解。该研究能弥补确定性问题研究的不足，使甩挂运输的研究更贴近实际，从而得到更加广泛的应用。

Container collection and distribution operations at the landside of the port are crucial for the whole port logistics system. Drop and pull transportation mode is an advanced operation mode for the container collection and distribution. When a container is towed to a customer’s location, the driver can drive the tractor to serve the next customer, leaving the trailer with container at the current customer’s location for (un)packing operation. The trailer with container can be pulled away by another tractor after the accomplishment of (un)packing. Under this mode, the (un)packing time required at customers directly impact the schedule of tractors. Nevertheless, because of the (un)packing time uncertainty in the implementation, the pre-generated tractor schedules using solid (un)packing time will always deviate, even become infeasible. This research intends to adopt robust optimization methods to investigate the container drayage problem with uncertain (un)packing time under drop and pull mode. Specifically, this research examines four types of uncertain (un)packing time, which include normal value based, interval based, scenario based and distribution based. Respectively, robust counterpart models are established and efficient algorithms are developed to obtain robust solutions under certain optimization criteria. This study can compensate for the shortages of certainty research, so as to make the research closer to reality and thus be more widely used.