Two-stage robust optimization for the integrated dynamic berth allocation and quay crane scheduling problem under uncertainty

A container port is an important cargo transit node that links the land and maritime regions, with berth allocation and quay crane scheduling tasks. Often, bad weather and delays in loading information make vessels' navigation uncertain. Therefore, in contrast to the classical berth allocation and quay crane assignment and scheduling problem, which minimizes the makespan, this study proposes a novel two-stage robust mixed-integer linear programming model for the integrated dynamic berth allocation and time-variant quay crane scheduling problem to minimize the total departure time, under uncertainties of vessel arrival time and container demand. An extended column constraint generation algorithm with a variable reduction strategy is designed to solve the model. Extensive computational experiments are performed to verify the effectiveness of the proposed model and algorithm. The conclusions drawn from this study could provide operational guidance for container operators to deal with uncertainties.