This paper puts forward an integrated optimisation model that combines three distinct problems, namely berth allocation, quay crane assignment, and quay crane scheduling that arise in container ports. Each one of these problems is difficult to solve in its own right. However, solving them individually leads almost surely to sub-optimal solutions. Hence, it is desirable to solve them in a combined form. The model is of the mixed-integer programming type with the objective being to minimize the tardiness of vessels and reduce the cost of berthing. Experimental results show that relatively small instances of the proposed model can be solved exactly using CPLEX. Large scale instances, however, can only be solved in reasonable times using heuristics. Here, an implementation of the genetic algorithm is considered. The effectiveness of this implementation is tested against CPLEX on small to medium size instances of the combined model. Larger size instances were also solved with the genetic algorithm, showing that this approach is capable of finding the optimal or near optimal solutions in realistic times.

中文翻译：

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集装箱港口中出现的海边作业的组合混合整数规划模型的进化方法

本文提出了一种综合优化模型，该模型结合了集装箱港口中出现的三个不同的问题，即泊位分配、岸桥分配和岸桥调度。这些问题中的每一个都很难单独解决。然而，单独解决它们几乎肯定会导致次优解决方案。因此，希望以组合的形式解决它们。该模型为混合整数规划类型，目的是最大限度地减少船舶的延误，降低靠泊成本。实验结果表明，使用 CPLEX 可以准确地求解所提出模型的相对较小的实例。然而，大规模实例只能在合理的时间内使用启发式方法解决。这里，考虑遗传算法的实现。此实现的有效性在组合模型的中小型实例上针对 CPLEX 进行了测试。还使用遗传算法解决了更大尺寸的实例，表明这种方法能够在现实时间内找到最佳或接近最佳的解决方案。