In today’s ports, the storage area is often the bottleneck in the serving of a vessel. It is therefore an important influencing factor in the minimization of the turnaround time of the vessels, which is the main objective in operational planning in container terminals. The operational planning of the yard cranes strongly impacts the yard’s efficiency. This planning task comprises the assignment of jobs to cranes, the sequencing of jobs per crane and the scheduling of crane movement and job executions subject to time windows and precedence constraints. A common yard configuration is a block storage system with two identical automated gantry cranes, called twin cranes. These cranes are subject to non-crossing constraints and therefore often exclusively serve either the landside or the seaside of the terminal. A polynomial-time algorithm for the scheduling subproblem of the cranes is introduced. As the sequencing and assignment part of this planning task is NP-hard, the overall problem is solved heuristically with a branch and bound procedure that includes the introduced scheduling algorithm as an evaluation subroutine. A computational study is presented to test the performance of this approach against a mathematical program solved by CPLEX.

中文翻译：

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基于分解的集装箱码头自动化堆场起重机调度方法

在当今的港口中，存储区往往是船舶服务的瓶颈。因此，它是最小化船舶周转时间的重要影响因素，这是集装箱码头运营规划的主要目标。堆场起重机的操作规划极大地影响堆场的效率。该计划任务包括将作业分配给起重机、每台起重机的作业排序以及受时间窗口和优先约束约束的起重机移动和作业执行的调度。常见的堆场配置是具有两个相同的自动化龙门起重机（称为双起重机）的块存储系统。这些起重机受到非穿越限制，因此通常专门服务于码头的陆侧或海边。介绍了起重机调度子问题的多项式时间算法。由于此规划任务的排序和分配部分是 NP 难的，因此使用分支定界过程启发式地解决了整个问题，该过程包括引入的调度算法作为评估子程序。提出了一项计算研究，以针对由 CPLEX 求解的数学程序测试此方法的性能。