The Container Relocation Problem for multiple bays consists of finding the minimum number of moves to load a set of stacked containers on a ship according to a given loading sequence, and in minimizing the crane’s working time for an entire yard of multiple bays. This is a crucial problem for every commercial port in the world given the maximum time requirements and the costs associated with the containers’ retrieval. In this paper, we propose a Greedy Randomized Adaptive Search Procedure to solve this problem. We use a myopic function specially designed to produce feasible candidate solutions with a structure that allows a local search procedure to optimize relocations. In order to validate our approach, we use a large set of well-known Container Relocation Problems for multiples bays, as well as a statistical analysis of our results. Our experiments show new bounds for various instances.

多个货柜的集装箱搬迁问题包括：根据给定的装载顺序找到将一组堆叠的集装箱装载到船上的最小移动次数，并最小化整个多个货柜的起重机的工作时间。考虑到最长的时间要求和与集装箱取回相关的成本，这对于世界上每个商业港口都是一个至关重要的问题。在本文中，我们提出了一种贪婪随机自适应搜索程序来解决这个问题。我们使用专门设计的近视功能来生成可行的候选解，其结构允许本地搜索过程优化重定位。为了验证我们的方法，我们对多个托架使用了许多众所周知的容器重定位问题，并对结果进行了统计分析。