Performance evaluation of In-Deep Class Storage for Flow-Rack AS/RS
Performance evaluation of In-Deep Class Storage for Flow-Rack AS/RS
复制标题
DOI：
10.1080/00207543.2011.624561
复制
发表时间：
2012-10
影响因子：
9.2
通讯作者：
O. Cardin;P. Castagna;Z. Sari;Nihad Meghelli
中科院分区：
文献类型：
--
作者：
O. Cardin;P. Castagna;Z. Sari;Nihad Meghelli
本文提出了一种新的存储检索方法，称为在深层类存储，设计用于流架AS/RS。基于类别的存储是一种众所周知的方法，有大量的文献;我们的方法是基于这样一个事实，即将每个箱子的前层专用于最受欢迎的物品类别，而不是将整个箱子专用于靠近落客站。显然，由于这种机架的动态行为，这个想法对于实现来说并不是微不足道的。因此，两个单独的算法已被定义，一个用于存储和检索，使动态使用我们的方法，与唯一的假设项目需求的帕累托分布。本文提出了一个模拟研究，旨在比较随机存储和检索的性能与使用的算法。这项研究表明，一个显着改善的预期检索延迟，主要的性能指标选择的研究。
This article presents a new storage-retrieval method called In-Deep Class Storage, designed for Flow-Rack AS/RS. Class-based storage is a well-known method that has an extensive literature; our method is based on the fact that it is more efficient to dedicate the front layers of each bin to the class of the most popular items rather than dedicating whole bins close to the drop-off station. Clearly, this idea is not trivial to implement due to the dynamic behaviour of such racks. Thus, two separate algorithms have been defined, one for storage and one for retrieval, enabling dynamic use of our approach, with the only hypothesis of a Pareto distribution of item demand. This article presents a simulation study designed to compare the performance of random storage and retrieval with the use of the algorithms. This study shows a significant improvement of the expected retrieval delay, the main performance indicator selected for the study.