遺傳演算法在物流中心儲位規劃之應用

A Study on the Storage Location Assignment in Distribution Center by Genetic Algorithm

王承新(Cherng-Shin Wang)

指導教授 ： 胡黃德

元智大學/工程學院/工業工程與管理學系/碩士(2000年)

摘要

目前台灣大多數的物流中心仍屬於勞力密集的作業，而揀貨作業為每日最主要之作業活動之一。合理的揀貨作業，對於物流中心的運作效率高低，具有決定性的影響，而良好的品項儲位指派規劃則為一種提昇揀貨效率的方式。在物流中心眾多品項裡，因相容性品項間將會形成一個品項群落；而每品項群落又需對應一個專屬之儲位群落，因此本研究針對物流中心品項儲位指派提出一個有儲位群落與品項群落限制之指派模式。本篇考量四種特定儲位佈置形態，配合訂單-品項-數量（EIQ）分析，了解品項間相依性與個別品項出現頻率，並利用遺傳演算法對於儲位指派之複雜組合最佳化問題，求得理想之品項儲位指派。研究結果顯示，含走道且出入口置走道中央之佈置形態具有較低之指派成本。

關鍵字

儲位指派 ； 訂單-品項-數量 ； EIQ ； 分析 ； 遺傳演算法

並列摘要

Most distribution centers (DCs) in Taiwan are still labor intensive, and the order picking operation is one of the important daily operations. A well-planned order picking operation can influence the efficiency of the daily operation of DC. Also, the planning of the storage location assignment can increase the efficiency of the picking operations. In DC, some of the various items would be gathered as an item cluster because of correlation, and each item cluster required a particular location cluster, Hence this study proposed a storage location assignment model which considered item and location cluster constraints. Four specific storage layout styles were applied, using entry-item-quantity (EIQ) analysis to figure out the frequency of single item and correlation between items on the orders. We also applied genetic algorithm procedure to obtain a better storage location assignment in this type of NP-Complete combinatorial problem. The result shows that the storage layout style, which contained cross aisle and I/O point located at the center of cross aisle, has lower average storage location assignment cost.

並列關鍵字

Storage Location Assignment ； Entry-Item-Quantity (EIQ) Analysis ； Genetic Algorithm

參考文獻

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