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A domain-specific knowledge-based heuristic for the Blocks Relocation Problem

机译:块重定位问题的基于特定领域知识的启发式方法

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The Blocks Relocation Problem consists in minimizing the number of movements performed by a gantry crane in order to retrieve a subset of containers placed into a bay of a container yard according to a predefined order. A study on the mathematical formulations proposed in the related literature reveals that they are not suitable for its solution due to their high computational burden. Moreover, in this paper we show that, in some cases, they do not guarantee the optimality of the obtained solutions. In this regard, several optimization methods based on the well-known A~* search framework are introduced to tackle the problem from an exact point of view. Using our A~* algorithm we have corrected the optimal objective function value of 17 solutions out of 45 instances considered by Caserta et al. (2012). In addition, this work presents a domain-specific knowledge-based heuristic algorithm to find high-quality solutions by means of short computational times. It is based on finding the most promising positions into the bay where to relocate those containers that are currently located on the next one to be retrieved, in such a way that, they do not require any additional relocation operation in the future. The computational tests indicate the higher effectiveness and efficiency of the suggested heuristic when solving real-world scenarios in comparison with the most competitive approaches from the literature.
机译:块重定位问题在于最小化龙门起重机执行的移动次数,以便根据预定顺序检索放置在集装箱堆场的托架中的一部分集装箱。对相关文献中提出的数学公式的研究表明,由于其计算量大,因此不适合其求解。而且,在本文中,我们表明,在某些情况下,它们不能保证所获得解的最优性。在这方面,介绍了几种基于众所周知的A〜*搜索框架的优化方法,以从确切的角度解决该问题。使用我们的A〜*算法,我们更正了Caserta等人考虑的45个实例中17个解的最佳目标函数值。 (2012)。此外,这项工作提出了一种基于特定领域知识的启发式算法,可以通过较短的计算时间来找到高质量的解决方案。它基于在海湾中找到最有前途的位置,将那些当前位于下一个要取回的容器中的容器重新放置,从而使它们将来不需要任何其他的重新放置操作。与文献中最具竞争力的方法相比,计算测试表明,在解决实际场景时,建议的启发式方法具有更高的有效性和效率。

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