DHMoGA BQCS : A Dynamic Heuristic Multi-Objective Genetic Algorithm for Berth Allocation and Quay Crane Assignment

Due to the increasing complexity of maritime logistics, the optimization of berth and quay crane scheduling in container terminals has become a critical issue in recent years. Existing algorithms often fail to integrate berth allocation with quay crane assignment, resulting in suboptimal solutions. Moreover, current coding strategies have difficulty balancing multiple objectives and adapting to dynamic port operations. Therefore, this paper proposes a novel dynamic heuristic multi-objective genetic algorithm for berth and quay crane scheduling problem (DHMoGABQCS), focusing on optimizing both vessel waiting time and berth deviations. The proposed DHMoGABQCSalgorithm includes the following three contributions. Firstly, a parking sequence-based coding (PSBC) strategy is developed to represent vessel arrival sequences and berthing positions, generating feasible solutions and improving efficiency. Secondly, a dynamic quay crane heuristic (DQH) strategy reallocates quay cranes based on vessel operation times to maximize utilization. Thirdly, the problem is formulated as a multi-objective optimization model, and a genetic algorithm framework is applied to balance vessel waiting times and berth deviations. Compared to other multi-objective optimization algorithms, the DHMoGABQCSalgorithm reduces the combined objective function value by 8.96% on average.