近年來由於網際網路的發達、消費型態的的轉變及世界經濟的全球化，使得物流的重要性大幅提升。然而物流業者為了能快速反應顧客多變的需求，期望能在正確的時點，運送正確數量與正確的商品到達客戶手中，所以傳統的物流模式已不再適用，必須有效地整合物流供應鏈，將傳統的多層級通路由「物流中心」取代，進而使物流中心成為一個極重要的角色。
在物流中心內的許多活動中，以「揀貨作業」是最耗費作業量與人力的一環，並且是與商品交期的準時、數量的正確性有最直接的關係。根據Coyle et al.(1996)的研究指出，揀貨作業占物流中心的總作業成本比例約達65%，是故，規劃一個合理的揀貨作業，對於物流中心的營運是有決定性的影響。
本研究欲探討的問題是物流中心的揀貨作業，其中將針對即時訂單批次的揀貨問題做探討，然而即時訂單批次所探討的因子包含：初始揀貨區選取(有4個水準)、配合揀貨區選取(有4個水準)、扣除品項選取(有2個水準)、批次訂單選取(有2個水準)，以及揀貨路徑(有2個水準)，共計有128種的實驗組合。吾人將藉由Visual C++ 8.0做模擬實驗，組合各不同因子的不同水準來進行實驗分析，並對系統模擬產生出的實驗數據以Excel 做輸出整理，最後以統計套裝軟體SPSS10.0 作一比較分析。以揀貨路徑距離為評估準則，期望得到一較佳的訂單批次組合方法，並對發展出之演算法作一結論，以及對未來研究方法的建議，以提供實體物流中心的揀貨作業有一參考依據。

This study deals with the real-time order-batching problem in a warehouse. In real-time order-batching, two or more orders are combined together in one picking list, and composition of the picking list is affected by the picker visiting pick-up point. A designed methodology divides this problem into five sub-problems is proposed. The sub-problems are to orderly determine the initial picking-zone, the appendant picking-zone, the minus items, the select orders, and the picking route. The simulation experience is measured by the total travel distance. We want to understand not only the performance of every main factor but also their combined performance. Different random problems were generated and tested for this purpose. It is hoped that the knowledge learned from this study can provide substantial benefits to practitioners in distribution centers.

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