低溫物流中心自動倉儲系統動態儲位指派之研究

Dynamic Assignment of Storage Spaces in Refrigerated Distribution Centers for Automated Storage/Retrieval System

近幾年世界各國在低溫食品上的銷售量呈現大幅成長的趨勢，而低溫物流中心是整個冷凍鏈中相當重要的一環，儲位指派作業又是影響物流中心整體作業效率的重要關鍵，尤其低溫食品腐敗的速度快，通常在選擇低溫物流中心區位時傾向選擇較靠近市場端之區位，但越靠近市場端之土地使用成本越高，故須提升低溫物流中心內的空間利用率以及作業上的效率。本研究將自動倉儲系統之動態儲位指派分做兩個階段進行，並分別構建可用線性規劃求解之模式，於第一階段指派先分析各種低溫食品隨著時間而快速腐敗之特性，而將越接近期限的低溫食品越先指派至中下游，且將過期之低溫食品移出儲位，進而瞭解空儲位分佈狀況；第二階段指派則考慮低溫食品具有需求量依時變動之特性，結合動態灰預測與第一階段指派之結果，將低溫食品指派至空儲位並使後續作業有效率地進行。最後，本研究以實務界常用之自動倉儲系統進行範例模擬分析，證明本研究所構建之儲位指派模式可提升物流中心的儲位利用率及作業上的效率。

In recent years, the sales volume of refrigerated food grew rapidly around the world. An efficient refrigerated distribution center is the key for success in the cold chain, and storage assignment is one of the most complicated and time-consuming activities among all processes in a refrigerated distribution center. In reality, locations near the market site are usually chosen due to perishable properties of refrigerated food, but the land values of these locations are much more expensive than those of other locations. Therefore, this study aims at formulating a model on dynamic assignment of storage space for efficiently increasing the utilization of storage spaces in a refrigerated distribution center with automated storage/retrieval system (AS/RS). The dynamic storage assignment is divided into two stages, and the model is constructed using the linear programming (LP) method. The first stage assignment assigns stored food to retailers and takes the overdue food out by analyzing the perishable properties of food according to its expiration time. The distribution of occupied and vacant spaces is identified in this stage. The second stage assignment combines the demand forecast results for various refrigerated items using dynamic grey predictions and the results of the first stage assignment. It continuously assigns different food items to empty spaces according to their forecasted demands. Finally, a simulated case study for an AS/RS practical system is provided to demonstrate the feasibility and the results of applying the proposed model. The results show that the model developed in this study can result in a higher space utilization as compared with the conventional models.