隨著科技的進步與市場型態的改變,企業為了提升服務水準與顧客滿意度,導致商品轉變成多樣化與客製化,因此倉儲的作業與管理上變得比以往來得更加複雜。為了因應倉儲作業的改變與改善其效率,自動化倉儲系統目前已逐漸地被應用在倉儲作業上。存取物料之動線規劃會影響到自動化倉儲系統之運作效率,因此本研究主要在探討存取動線規劃之問題。物料存取之動線規劃屬於NP-hard問題,基因與免疫演算法於此類型問題中具有優越的求解能力,因此本研究利用此兩種演算法作為求解的方法。由於自動化倉儲系統的複雜程度受到存取機載量、存貨架數量、出入庫位置此三項基本設備之影響,本研究藉由此三項變因不同的組合以代表不同複雜度之自動化倉儲系統,利用基因與免疫演算法的求解能力進行系統中物料存取動線的規劃。本研究根據學者李智信(2000)所提出的測試實驗問題,藉由不同的問題類型,透過基因與免疫演算法求解後,並將測試結果與過去文獻(陳世泓,2006)作比較,數據結果顯示,對於全部測試問題免疫演算法可獲得優於文獻的目前最佳解,而基因演算法亦有不錯的結果。另外為更符合實際業者需求,改變演算法之限制條件以限定程式運作需花費時間,結果發現在問題複雜度較低時,基因與免疫演算法其求解的結果,仍優於過去文獻(陳世泓,2006)之蟻群最佳化演算法。
An automated storage and retrieval system (AS/RS) is a storage system that uses fixed-path storage and retrieval machines running on one or more rails between fixed arrays of storage racks. A dual command AS/RS operation involves S/R machine picking up a load at the I/O point, traveling to an empty location, depositing the load, traveling empty to the location of the desired retrieval, picking up the load, traveling to the I/O point. The storage-retrieval sequencing is an important issue in a dual command AS/RS. In order to improve efficiency without modifying the existing AS/RS, this study used two methodologies, Genetic Algorithm and Immune Algorithm, to decide the storage-retrieval sequencing. The previous work which using Ant Colony Optimization(陳世泓,2006) was used as a benchmark. The two algorithms were tested in 10 configurations of AS/RS, and the results show that Immune Algorithm can find the better sequencing than Genetic Algorithm and Ant Colony Optimization in most configurations.