Integrated berth and quay crane allocation problem (BQCAP) are two essential seaside operational problems in container terminal scheduling. Most existing works consider only one objective on operation and partition of quay into berths of the same lengths. In this study, BQCAP is modeled in a multiobjective setting that aims to minimize total equipment used and overall operational time and the quay is partitioned into berths of different lengths, to make the model practical in the real-world and complex quay layout setting. To solve the new BQCAP efficiently, a multiobjective hydrologic cycle optimization algorithm is devised considering problem characteristics and historical Pareto-optimal solutions. Specifically, the quay crane of the large vessel in all Pareto-optimal solutions is rearranged to increase the chance of finding a good solution. Besides, worse solutions are probabilistic retained to maintain diversity. The proposed algorithm is applied to a real-world terminal scheduling problem with different sizes from a container terminal company. Experimental results show that our algorithm generally outperforms the other well-known peer algorithms and its variants on solving BQCAP, especially in finding the Pareto-optimal solutions range.

中文翻译：

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基于多目标水文循环优化的不同泊位规模的综合集装箱码头调度问题

综合泊位和岸桥分配问题 (BQCAP) 是集装箱码头调度中的两个重要的海边作业问题。大多数现有工作只考虑一个目标，即运营和将码头划分为相同长度的泊位。在这项研究中，BQCAP 在多目标环境中建模，旨在最大限度地减少总设备使用量和总体运营时间，并将码头划分为不同长度的泊位，使模型在现实世界和复杂的码头布局环境中具有实用性。为有效求解新的BQCAP，结合问题特征和历史帕累托最优解，设计了多目标水文循环优化算法。具体来说，对所有帕累托最优解中的大型船舶的岸桥进行重新排列，以增加找到良好解的机会。此外，更差的解决方案被概率保留以保持多样性。所提出的算法应用于来自一家集装箱码头公司的不同规模的真实码头调度问题。实验结果表明，我们的算法在求解 BQCAP 方面通常优于其他著名的同类算法及其变体，尤其是在寻找帕累托最优解范围方面。