臺灣博碩士論文加值系統

物流中心的揀貨作業時間約佔物流中心總作業時間的40% ~ 60%，揀貨作業直接相關的人力佔了50%以上，揀貨人工作業成本則為物流經營總成本的15% ~ 20%。湯普金等人亦指出揀貨行進時間佔了揀貨人員約50%的揀貨時間。因此揀貨作業效率化是物流中心達成高頻、快速配送的關鍵所在。儲位規劃包括儲位配置、揀貨方法與儲位指派，為提高揀貨效率、降低揀貨作業的成本可自這三方面著手。揀貨作業所耗費的時間，主要分為巡行時間或物品移動時間、物品扱取時間與物品尋找時間。在揀貨作業過程中，巡行及尋找的時間所佔比例愈少，效率愈高。
為能將揀取作業量高的品項更集中於揀貨區中央通道及前端靠近分貨合流點位置的目的，本研究考量綜合法揀貨途徑策略的特色，擷取通道間法及橫越法的特點建構混合法儲存政策。模擬結果顯示，混合法較對角法等儲存政策可減少 1.03% ~ 5.90% 的平均巡行距離，在高需求偏態下更高達13.66% ，且在99%的信賴水準下與各儲存政策的平均巡行離均有顯著差異。在實務應用上，需求非常集中在某些少數品項、不論是在寬扁型或是狹長型的庫儲作業區型態下，如採取綜合法為途徑策略，混合法儲存政策可有最低的巡行距離。

According to the report of the Ministry of Economics, the operating time of order picking almost occupied 40 percent to 60 percent of total operation cost in a Distribution Center, and the relative direct labor cost is more than 50 percent of it. Total of all, the labor cost of order picking constitutes 15 to 20 percent of total running cost of a Distribution Center. In addition, Tompkins’ research shows that the traveling time of order picking in a warehouse is about 50 percent of order picking operation.
Storage planning consists of storage allocation, storage assignment, and order picking method, and it affects the efficiency of order picking operation significantly. Therefore, we are able to promote the efficiency of order picking operation and reduce its operating cost from these three aspects.
To concentrate the high volume items in the middle aisles and front locations, we construct Hybrid storage policy, which combine the features of Within-Aisle and Across-Aisle. The result shows that Hybrid policy can save up to 13.66 percent of traveling distance, especially in a high demand skewness and wider warehouse. The pairwise comparisons of mean difference are significant under 99% confidence interval. Additionally, Hybrid is outperformed with Composite routing heuristic.

摘 要I
英文摘要II
誌 謝III
目 錄IV
圖目錄VI
表目錄VII
第一章緒論1
1.1 研究動機與目的1
1.2 研究問題與基本假設2
1.2.1 研究問題2
1.2.2 基本假設2
1.3 研究方法、研究流程與模式架構3
第二章文獻探討6
2.1 儲存政策6
2.1.1對角法(Diagonal)6
2.1.2通道間法(Within-Aisle)7
2.1.3橫越法(Across-Aisle)7
2.1.4週緣法(Perimeter)7
2.2 儲位指派法則10
2.2.1以週轉率(Turnover-Based Location)為基礎法則10
2.2.2以揀取頻次(Frequency)為基礎之法則10
2.2.3訂單體積指標法(Cube-per-Order Index, CPO)11
2.2.4訂單-品項-數量分析法(Entry-Item-Quantity, EIQ)12
2.3 揀貨途徑策略13
2.3.1穿越法(Transversal)15
2.3.2折返法(Return)15
2.3.3中點法(Midpoint)15
2.3.4 最大間隙法(Largest Gap)16
2.3.5 綜合法(Composite)16
第三章倉儲系統模擬架構18
3.1 庫房配置與分類假設18
3.2 儲位配置20
3.3 揀貨巡行距離計算及範例22
3.3.1穿越法23
3.3.2折返法25
3.3.3中點法27
3.3.4最大間隙法29
3.4.5綜合法31
第四章模擬結果33
4.1 揀取品項頻次分布35
4-2 寬型庫儲存假設下的巡行距離40
4-3 不同庫儲型態之巡行距離43
第伍章結論與未來研究方向50
5.1 結論50
5.2 未來研究方向51
參考文獻52
附錄一、各途徑策略平均巡行距離差異比較i
附錄二、各儲存政策在不同庫儲型態下的執行結果ii
附錄三、各儲存政策以綜合法為途徑策略比較表xi

[1] 王麗慧，民88年，「物流中心儲位指派與揀貨順序整合模式之研究」，臺灣科技大學碩士論文
[2] 林文彬、許明霖，1995，「自動化物流中心系統模擬之實證研究」，全國自動化科技研討會
[3] 林國傑、潘昭賢，民88年，「物流中心物品儲位指派之研究」，管理與系統，卷六第二期，pp. 131 - 150
[4] 董福慶、陳明德，1995，「物流中心揀貨作業」，經濟部商業司
[5] 劉浚明，1996，「儲位規劃和揀貨作業設計以改善物流中心效率」，國際商業物流管理研討會論文集，pp. 485-490
[6] 鍾雲恭編譯，民72年，Billy E. Gillett原著，”Introduction to Operations Research —A computer-oriented Algorithm Approach”，臺北，松崗
[7] 簡美珍、陳振明，1996，「物流中心揀貨作業最佳儲位規劃」，國際商業物流管理研討會論文集，pp. 330-338
[8] Barrett, B.G., 1977, ”An Empirical Comparison of High-Rise Warehouse Policies for Operator-Controlled Stacker Cranes”, Interfaces, Vol. 8, No.1, pp. 46-49
[9] Coyle, J.J., Bardi, E. J. and Langley, C.J., 1996, “The Management of Business Logistics”, West, St Paul, MN
[10] Goetschalckx, M. and Ratliff, H. D. 1988a, “Order picking in an aisle”, IIE Transactions, Vol. 20, No. 1, pp. 53-62
[11] Hall, Randolph.W., 1993, “Distance approxiamations for routing manual pickers in a warehouse”, IIE Transactions, Vol. 25 No. 4, pp. 76-87
[12] Harmatuck, D. J., 1976, “A comparison of Two Approaches to Stock Locations”, The Logistics and Transportation Review, Vol. 12, No. 4, pp. 27-31
[13] Hausman, W.H., Sgwarz, L.B., & Graves, S.C., 1963,”Optimal Storage Assignment in Automatic Warehousing Systems”, Management Science, Vol. 9, No. 1, pp.27-31
[14] Heskett, W.H., 1963, “Cube-Per-Order Index—A Key to Warehouse Stock Location”, Transportation and Distribution Management, Vol. 9, No. 1, pp. 27-31
[15] Jarvis, J. M. & McDowell, E. D., 1991, “Optimal product layout in an order picking warehouse”, IIE Transaction, Vol. 25, No. 4, pp. 93-102.
[16] Linn, R.J. & Wysk, R.A., 1987, “An Analysis of Control Strategies for Automated Storage and Retrieval Systems”, INFOR, Vol. 25, No.1, 1987, pp.66-83
[17] Petersen II, Charles G., 1995, “Routeing and storage poicy interaction in order picking operations”, Decision Sciences Institute Proceedings, Vol. 3, pp. 1614 - 1616
[18] Petersen II, Charles G., 1997, “An evaluation of order picking routing policies”，IJOPM, Vol. 17, No. 11, pp. 1098 - 1111
[19] Petersen II, Charles G., 1999, “The impact of routing and storage policies on warehouse efficiency”, IJOPM, Vol. 19, No. 10, pp. 1053-1064
[20] Petersen II, Charles G. Roger W. Schmenner, 1999, ”An Evaluation of Routing and Volume-based Storage Policies in an Order Picking Operation”, Decision Sciences, Vol. 30, No. 2, pp. 481─501
[21] Rana, Krishan, 1991, “Order Picking in Narrow-Aisle Warehouses”, International Journal of Physical Distribution & Logistics Management, Vol. 20, No. 2, pp. 9-15
[22] Tompkins, J.A., White, J.A., Bozer, Y.A., Frazelle, E.H., Tanchoco, J.M.A. and Trevino, J., 1996, “Facilities Planning”, John Wiley, New York, NY.