分區式揀貨系統之訂單批次化問題研究

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蔡冠右(Kuan-You,Tsai) 查詢紙本館藏

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分區式揀貨系統之訂單批次化問題研究

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摘要(中)

近年來，網路購物迅速發展，「宅經濟」大流行，促使消費管道從原先實體店面轉移到電商平台。購物型態的改變也提升了物流的難度，網購商家主打的24小時快速到貨及與日俱增的配送量考驗著物流中心的產能與效率，快速反應消費者的需求已是物流中心必備的條件，如何在滿足客戶需求的同時降低成本成為物流中心面臨的一大考驗。
物流中心的作業流程可歸類為下列九項：進貨、搬運、儲存、盤點、訂單、揀貨、補貨、出貨、輸配送，其中揀貨作業是最具客戶敏感度的一環，同時也是耗費作業量以及人力最大的一項工作。目前大多數的物流中心是屬於「勞力密集」的產業，揀貨作業占物流中心運營總成本的50-75%，為物流中心「成本最高的作業流程」，且揀貨作業時間佔整個物流作業時間約30-40%。是故，如何優化揀貨流程為物流中心的首要目標。
以往，普遍物流中心的揀貨方式為「個別揀取」，即一位揀貨員一次揀取一張訂單，此法的優點是很簡單，缺點則是較沒有效率。對此，常見的解決方式為「批次揀取」，意即將相似訂單合併處理，一個揀貨員同時對多張相似訂單進行揀貨，減少揀貨作業時間。訂單批次化的優劣對批次揀貨有關鍵影響，好的訂單批次化方法對揀貨效率有顯著幫助。
然而，過往的訂單批次化文獻，研究環境相對單一，鮮少探討物流業常見的「分區式揀貨系統」。此揀貨系統具有揀貨行走路線流暢的優點，缺點為動線複雜，搭配優秀的揀貨策略顯得格外重要。基於上述原因，本研究將針對分區式揀貨系統中的揀貨策略進行研究，探討訂單批次化問題。此外，為了更進一步提升揀貨效率，本研究同時探討訂單批次選取問題與動態式揀貨路徑問題，與訂單批次化問題共同探討，找出最適合的揀貨策略搭配，並期望透過完整的模擬實驗與績效分析，增加對此類問題的了解，對未來的類似研究，也將有相對之貢獻。

摘要(英)

In recent years, online shopping has developed rapidly, and the "Stay-at-Home Economy" has prompted the shift of consumer channels from the retailer to e-commerce platforms. Changes in shopping patterns have also increased the difficulty of logistics. The 24-hour fast delivery and increasing delivery volume of online shopping test the logistic efficiency. Quick response to consumer needs is a necessary ability to distribution centers.
Among all operation of the distribution center, order picking is the most workload and manpower operation. At present, most distribution centers are "labor-intensive" industry. Order picking account for about 50-75% of the total operating costs, and the order picking time is about 30-40% of the total operating time. Therefore, how to optimize the order picking process is the primary goal of the distribution center.
In the past, the general order picking method was "individual picking", that is, one picker picks one order at a time. The advantage of this method is that it is very simple, but the disadvantage is that it is less efficient. In this regard, the common solution is "batch picking", which means that similar orders are merged to same order batch and opereted together, so a picker can pick multiple similar orders at the same time, reducing the picking time. The pros and cons of order batching have a key impact on batch picking.
However, in the past literature on order batching, the research environment was relatively single and seldom discussed the "zone picking system". This picking system has the advantages of a smooth picking route, but the disadvantage is that the picking traffic flow is complicated, and it is important to match an excellent picking strategy. Based on the above reasons, this research will study the picking strategy in the zone picking system, and mainly discuss the order batching problem. In addition, in order to further improve the efficiency, this research also discusses the order batch selection problem and dynamic order picking routing problem, and find the most suitable picking strategy. It is hoped that through complete simulation experiments and statistical analysis, it will increase the understanding of order picking issues.

關鍵字(中)

★ 物流中心
★ 分區式揀貨系統
★ 訂單批次化
★ 訂單批次選取
★ 動態式揀貨路徑

關鍵字(英)

★ Distribution Center
★ Zone Picking System
★ Order Batching
★ Order Batch Selection
★ Dynamic Order Picking Route

論文目次

摘要 I
Abstract II
目錄 III
圖目錄 VI
表目錄 VIII
第一章緒論 1
1.1 研究背景 1
1.2 研究動機 2
1.3 研究目的 3
1.4 研究環境 4
1.5 論文架構 7
第二章文獻探討 9
2.1 倉儲規劃（Warehouse planning） 9
2.1.1 倉儲設計（Warehouse design） 9
2.1.2 走道設計（Aisle design） 14
2.2 儲位規劃（Storage planning） 17
2.2.1 儲位指派（Storage assignment） 17
2.2.2 儲區佈置（Warehouse layout） 20
2.3 訂單揀貨規劃（Order picking planning） 26
2.3.1 訂單批次化（Order batching） 26
2.3.2 揀貨政策（Picking policy） 34
2.3.3 路徑策略（Routing strategy） 38
第三章研究方法 45
3.1 問題說明 45
3.2 方法架構與流程 45
3.3 訂單批次化問題 47
3.3.1 種子訂單+配合訂單選擇法 47
3.3.2 種子訂單選擇法 50
3.3.2.1 揀貨區域數最少法 51
3.3.2.2 平均揀貨區域懲罰值最小法 52
3.3.2.3 揀貨區域重心與I/O點之直線距離最短法 54
3.3.2.4 最小方形揀貨覆蓋區域法 55
3.3.2.5 揀貨區域與I/O點之平均直線距離最短法 57
3.3.3 配合訂單選擇法 60
3.3.3.1 額外增加揀貨區域數最少法 61
3.3.3.2 平均揀貨區域懲罰值差異最小法 62
3.3.3.3 訂單間揀貨區域重心之直線距離最短法 64
3.3.3.4 最大揀貨覆蓋區域重疊面積法 66
3.3.3.5 訂單間揀貨區域至最鄰近揀貨區域之平均相互直線距離最短法 68
3.4 訂單批次選取問題 74
3.4.1 最大未重複揀貨區域數與重複揀貨區域數之比例法 76
3.4.2 最小漸增權重懲罰值法 78
3.4.3 最大漸增權重加權值法 79
3.5 揀貨區域拜訪順序問題 82
3.5.1 動態揀貨區域拜訪順序法 82
3.5.2 鄰近揀貨區域優先演算法 85
3.5.3 模擬退火演算法 85
3.5.4 模擬退火演算法設置 87
第四章模擬實驗與分析 88
4.1 模擬實驗設計 88
4.1.1 揀貨環境設定 88
4.1.2 實驗訂單設定 90
4.1.3 揀貨環境假設 90
4.1.4 實驗因子組合 91
4.2 績效評估指標 93
4.3 統計分析 93
4.3.1 分析說明 94
4.3.2 依「揀貨系統總執行時間（TST）」為績效評估指標 94
4.3.2.1 個別因子之說明（依TST績效值） 95
4.3.2.2 不同因子交互作用之說明（依TST績效值） 99
4.3.2.3 最佳因子組合與績效（依TST績效值） 107
4.3.3 依「揀貨員總揀貨距離（TTD）」為績效評估指標 123
4.3.3.1. 個別因子之說明（依TTD績效值） 124
4.3.3.2. 不同因子交互作用之說明（依TTD績效值） 127
4.3.3.3. 最佳因子組合與績效（依TTD績效值） 140
4.3.4 依「揀貨員總忙碌時間（TBT）」為績效評估指標 152
4.3.4.1 個別因子之說明（依TBT績效值） 153
4.3.4.2 不同因子交互作用之說明（依TBT績效值） 156
4.3.4.3 最佳因子組合與績效（依TBT績效值） 170
4.4 實驗結論 182
第五章研究結論與建議 185
5.1 研究結論 185
5.2 未來研究建議 187
參考文獻 189
中文文獻 189
英文文獻 190

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指導教授

何應欽(Ying-Chin Ho)

審核日期

2021-7-28

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