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首页> 外文期刊>Transportation Science >Polynomial Time Algorithms to Minimize Total Travel Time in a Two-Depot Automated Storage/Retrieval System
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Polynomial Time Algorithms to Minimize Total Travel Time in a Two-Depot Automated Storage/Retrieval System

机译:多项式时间算法可最大限度地减少两仓库自动存储/检索系统中的总旅行时间

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We sequence storage and retrieval jobs to minimize total travel time of a storage/retrieval (S/R) machine in a two-depot automated storage/retrieval system. These systems include storage systems with aisle-captive S/R machines and storage blocks with bridge cranes. The S/R machine must move retrieval unit loads from their current locations in the system to one of the two depots. In addition, it must move storage unit loads from given depots to given locations in the system. We model the problem as an asymmetric traveling salesman problem, which is in general NP-hard. We develop an algorithm to solve the problem in polynomial time, using the property that the system has two depots and the S/R machine always returns to one of the depots to pick up or deliver a load. Furthermore, we develop additional polynomial time algorithms for the following four special cases: (1) retrieval loads have to be delivered to given depots; (2) the system has one input depot and one output depot; (3) the system has a single depot; and (4) there are arbitrary S/R machine starting and ending locations. The computational results show the effectiveness of the proposed algorithms. Compared to first-come-first-served and nearest neighbor algorithms, commonly used in practice, the total travel time reduces on average by more than 30% and 15%, respectively.
机译:我们对存储和检索作业进行排序,以最大程度地减少两仓库自动存储/检索系统中存储/检索(S / R)机器的总行驶时间。这些系统包括带有过道防盗S / R机器的存储系统和带有桥式起重机的存储块。 S / R机器必须将检索单元的负载从它们在系统中的当前位置移动到两个仓库之一。另外,它必须将存储单元的负载从给定的仓库移至系统中的给定位置。我们将该问题建模为一个不对称的旅行推销员问题,通常是NP-难问题。我们开发了一种算法来解决多项式时间内的问题,它利用系统具有两个仓库,并且S / R机器总是返回到其中一个仓库来接载货物的特性。此外,我们针对以下四种特殊情况开发了其他多项式时间算法:(1)检索负载必须交付给给定的仓库; (2)系统具有一个输入库和一个输出库; (3)系统有一个仓库; (4)有任意S / R机器的开始和结束位置。计算结果表明了所提算法的有效性。与通常使用的先到先服务和最近邻居算法相比,总旅行时间平均分别减少了30%和15%以上。

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