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An optimal and a heuristic algorithm for the single-item retrieval problem in puzzle-based storage systems with multiple escorts

机译:具有多个伴游的基于拼图的存储系统中单项检索问题的最优启发式算法

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摘要

Puzzle-based storage systems consist of densely stored unit loads on a square grid. The problem addressed in this paper is to retrieve a stored unit load from a puzzle-based storage using the minimum number of item moves. While previous research contributed optimal algorithms for only up to two empty locations (escorts), our approach solves configurations where multiple empty locations are arbitrarily positioned in the grid. The problem is formulated as a state space problem and solved to optimality using an exact search algorithm. To reduce the search space, we derive bounds on the number of eligible empty locations and develop several search-guiding estimate functions. Furthermore, we present a heuristic variant of the search algorithm to solve larger problem instances. We evaluate both solution algorithms on a large set of problem instances. Our computational results show that the algorithms clearly outperform existing approaches where they are applicate and solve more general configurations, which could not be solved to optimality before. The heuristic variant efficiently yields high-quality solutions for significantly larger instances of practically relevant size.
机译:基于拼图的存储系统由在正方形网格上密集存储的单位负载组成。本文解决的问题是使用最少数量的物品移动从基于拼图的存储中检索存储的单位负载。尽管先前的研究仅针对最多两个空白位置(护卫队)提供了最佳算法,但我们的方法解决了在网格中任意放置多个空白位置的配置。该问题被公式化为状态空间问题,并使用精确搜索算法求解为最优。为了减少搜索空间,我们导出了符合条件的空位置的数量范围,并开发了几种搜索指导估计函数。此外,我们提出了搜索算法的启发式变体来解决较大的问题实例。我们在大量问题实例上评估两种解决方案算法。我们的计算结果表明,该算法明显优于现有方法,适用于现有方法并且可以解决更一般的配置,而这是以前无法解决的。启发式变量可以有效地产生高质量的解决方案,以用于实际相关尺寸的较大实例。

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