The performance of a container terminal heavily relies on how efficiently the quayside resources, which are mainly berth and quay cranes, are used. The quayside related planning problems face uncertainty in various parameters, and this makes the efficient planning of these operations even more complicated. This study aims at developing a recoverable robust optimization approach for the weekly berth and quay crane planning problem. In order to build systematic recoverable robustness, a proactive baseline schedule with reactive recovery costs has been suggested. The uncertainty of vessel arrivals and the fluctuation in the container handling rate of quay cranes are considered. The baseline schedule includes berthing positions, times and quay crane assignments for all vessels along with vessel-specific buffer times and buffer quay cranes. The problem also introduces recovery plans for each scenario. The objective is to minimize the cost of baseline schedule, the recovery costs from the baseline schedule and the cost of scenario solutions for different realizations of uncertain parameters. A mathematical model and an adaptive large neighborhood based heuristic framework are presented to solve the novel problem. Computational results point out the strength of the solution methods and practical relevance for container terminals.
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