以分群為基礎之訂單批量化方法探討

A study on cluster-based of order batch methods

邱耀弘(yao-hung chiu)

指導教授 ： 何應欽

國立中央大學/管理學院/工業管理研究所/碩士(2008年)

摘要

摘要
隨著新的價值觀與消費型態的萌生，企業為降低中間轉運費用，節省管理及倉儲成本，使得物流中心的設立與需求，將成為必然的發展趨勢。物流中心的主要功能係將商品集中並分散至零售業，目的在於增快貨品流通速度並避免不必要的運儲成本，使商品能快速運送到達顧客手中。
許多統計資料顯示，整個物流作業在公司的營運成本中，佔了相當大的比例。大多數的物料處理作業，都是屬於勞力密集且高重複性；產品的揀貨作業策略，又直接地影響了企業營運成本的高低。從人工需求的角度來看，其中揀貨作業直接相關的人力更佔 50% 以上，由此可見規畫合理的揀貨作業，對於日後物流中心的運作效率高低，具有決定性的影響。
本研究將在揀貨員進行揀貨動作前，作一訂單批次化，使相類似之訂單可以在同一揀貨車旅程中被揀取，以期達到較高之揀貨效率；過程中透過Visual Basic 6.0作模擬實驗，比較訂單在不同相似係數下並搭配不同分群方式配合不同滿足揀貨車容量的方式，來比較批次化的差異，再利用SPSS 12.0軟體作統計分析，並評估揀貨旅程路徑之長短，來求得較佳之因子組合，進而對發展出之演算法作一結論，以及對未來研究方向之相關建議，以供實體物流中心揀貨作為參考之依據。

關鍵字

物流中心 ； Fuzzy c-means ； 訂單切割法則 ； 相似係數

並列摘要

In this paper, we look into one of the problems that one often encounters in the order picking of distribution centers. This problem is known as order-batching problem. In an order-batching problem, one has to select two or more orders, batch them, and pick their requested items at the same order-picking trip. Order-batching problem is an important problem in distribution centers that often have to handle many different orders in one day. This is because one can reduce the total travel distance if orders with similar picking locations are batched and picked together. And, the order-picking cost can be reduced as a result. The proposed order-batching method has three major steps to form an order batch. At the first step, similar coefficient of orders between each other will be produced from the order pool. At the second step, Use of different similar coefficients to do fuzzy c-means clustering in order to do so after picking batch of orders. In order batch method also divided into two modes of doing, were known as the "single group" and "multi-groups," and after to compare their advantages and disadvantages. Finally, loading Picking on the car, also used the three batches of ways to carry. For this problem, we propose five different similar coefficients rules, We also propose two different modes for the order batch problem. Furthermore, we also propose three loading methods to order-picking for an order batch. Test problems are then generated and solved by each one of them. Their solution results are collected and compared to see which similar coefficients rule, which order batch mode, which loading method, and what combination of them can result in the best performance in minimizing the total travel distance. It is hoped that the knowledge learned from this study can provide substantial benefits to practitioners in distribution centers.

並列關鍵字

fuzzy c means ； Distribution Center ； similar coefficient

參考文獻

3. Barrett, B. G., 1977, “A further digression on the over-automated warehouse: some evidence,” Interfaces, vol. 8, no.1, pp. 46-49.

4. Bassan Y., Roll Y., Rosenblatt M. J., 1980, “Internal Layout Design of a Warehouse,” AIIE Transactions, Vol.12, pp317-322.

6. Bozer, Y. A., 1986, “Optimizing throughput performance in designing orderpicking systems,” Ph.D. Dissertation, Georgia Institute of Technology, Atlanta,G.A.

7. Brynzer. H. and Johansson. M. I, 1995, “Design and performance of kitting and orderpicking systems,” International Journal of Production Economics, vol. 41, pp.115-125

8. Brynzer, H., and Johansson, M. I., 1996, “Storage location assignment: Using the product structure to reduce order picking times,” International Journal of Production Economics, vol. 46-47, pp. 595-603.