Integrated berth allocation and quay crane assignment considering pandemic-induced disruptions: a decomposition-based optimization

To address the scheduling complexities arising from quarantine procedures and infection risks during major public health emergencies, a two-stage robust optimization model that integrates the berth allocation and quay crane assignment problem, and aims to minimize total costs, including vessel anchoring, delay and stochastic recourse costs, was developed, and the impact of fluctuations in the quarantine duration on terminal operations was characterized. To solve this problem efficiently, a nested framework combining column and constraint generation (C&CG) and column generation (CG) was designed. This framework ensures both the robustness of the solution and computational efficiency by identifying worst-case scenarios and managing large numbers of decision variables. The results of numerical experiments demonstrate that the proposed algorithm significantly reduces total costs and outperforms commercial solvers in solving large-scale instances. Sensitivity analysis reveals the scaling patterns of workgroup configurations under different epidemic prevention and control levels.