單批量策略是用來決定如何結合訂單以形成批量的方式。若訂單以相似揀貨路經來整合成一個批量並且在一相同訂單揀貨路徑下被揀取，則此訂單批量可以有效降低所以訂單完成的時間以提升整體之作業效率。因為訂單批量是一個NP-hard問題，此篇論文將提出一個基於模糊相似度叢集的啟發式演算法分別用於返回、穿越與最大間隙等三種行走路徑策略下。二筆訂單的相似程度可以藉由模糊相似度方法被判斷。如此一來使得演算法在訂單批量問題上能獲得較佳的解。演算法的真實效率，本文將與其他目前所提出之演算法透過電腦模擬方式來做比較。其結果指出我們所提出之演算法策略具有更好的績效。然而，我們所提出之演算法在實務上是簡單且容易被接受的。

Order batching policy decide the method to combine order to form batch. If the orders with similar picking location are integrated into a batch and are picked in the same picking tour, the order bathing can reduce the total distance of all order finished and promote the efficiency of operation in the manual order picking system. Since batching is an NP-hard problem, this paper proposes a heuristic algorithms base on fuzzy similarity clustering for each of the three routing policies, return, traversal and largest gap. The similar degree of two orders can be recognized effectively by fuzzy similarity. This enables the heuristic to attain the better solution for order batch problem. To verity the efficiency of the heuristic, this paper compares other existing algorithms through computer simulation. The result indicates that the proposed heuristic algorithm has batter performance. Furthermore, the algorithm is quite simple and can be easily applied in practice.

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