分區式揀貨倉庫之訂單批次化問題探討

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蔡昕頤(Hsin-Yi Tsai) 查詢紙本館藏

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工業管理研究所

論文名稱

分區式揀貨倉庫之訂單批次化問題探討

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摘要(中)

近年來，網路購物的迅速發展，消費管道由實體店面轉移至電商平台，更因COVID-19（新冠肺炎）疫情席捲全球，零售業網路銷售額屢創新高，而網購商家所主打的24小時快速到貨及與日俱增的配送量，皆考驗著物流中心的產能與效率。因此，如何在快速滿足客戶需求的同時降低成本，儼然成為物流中心的一大挑戰。
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，同時也是作業量與人力耗費最大的一項工作。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至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至40%。是故，優化揀貨流程成為物流中心的首要目標。
以往，物流中心的揀貨方式普遍為「個別揀取」，即一位揀貨員一次揀取一張訂單，此法的優點是簡單明瞭，缺點則是效率較低。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，以減少揀貨作業時間與所需行走距離，由此可見，訂單批次化的優劣對揀貨效率將產生關鍵影響，若能找到適合的訂單批次化方法勢必能顯著提升揀貨效率。
然而，過往的訂單批次化相關文獻，鮮少探討物流業常見的「分區式揀貨系統」。此揀貨系統的揀貨行走路線流暢，但隨之而來的是動線相較複雜，因此搭配優良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批次化問題進行研究，並期望透過完整的模擬實驗與嚴謹的績效分析，能對此類問題有更深入的探討，亦對未來類似的研究能有所貢獻。

摘要(英)

Nowadays, online shopping has rapidly developed, and the "Stay-at-Home Economy" has accelerated the alteration of consumer behavior from the retailer to e-commerce platforms. Due to this situation, the change of shopping mode has increased the difficulty of logistics. The 24-hour fast delivery and the increasing volume of online shopping test the logistic efficiency. Response instantly 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 takes 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 conducts one order at a time. The advantage of this method is simple to complete for those manipulators, 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 be operated by pickers together, so a picker can select multiple and similar orders at the same time, reducing the picking time. The pros and cons of order batching impacts significantly.
However, in past essay about order batching, the research environment was relatively single and seldom discussed "zone picking system". This kind of picking system has a prime merit, smooth picking routes, but the disadvantage is that the picking traffic flow is much more complicated. It is important to match an excellent picking strategy. Based on the reasons above, this research will study the picking strategy in zone picking system, and will mainly discourse the order batching problem. In addition, in order to improve the efficiency, this research will also state the order batch selection problem and dynamic order picking routing problem, and finally find the most suitable picking strategy. Expecting that through this complete simulation experiments and statistical analysis can increase the understanding of order picking issues for the future of distribution center.

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 4
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） 35
2.3.3 路徑策略（Routing strategy） 40
第三章研究方法 48
3.1 問題說明 48
3.2 方法架構與流程 48
3.3 訂單批次化問題 50
3.3.1 種子訂單+配合訂單批次化法 51
3.3.2 種子訂單選擇法 53
3.3.2.1 揀貨區域數最少法 54
3.3.2.2 最小方形揀貨覆蓋區域法 55
3.3.2.3 揀貨區域中心點與I/O點之平均直線距離最短法 56
3.3.2.4 揀貨區域中心點與I/O點之平均矩形距離最短法 60
3.3.2.5 以NPZF產生之拜訪順序為基礎的揀貨路徑旅行距離最小法 62
3.3.3 配合訂單選擇法 68
3.3.3.1 額外增加揀貨區域數最少法 68
3.3.3.2 最大揀貨覆蓋區域重疊面積法 69
3.3.3.3 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 71
3.3.3.4 訂單間揀貨區域至最鄰近揀貨區域之平均相互矩形距離最短法 77
3.3.3.5 增加額外旅行距離最小法 82
3.3.3.6 旅行距離成本相似係數最大 87
3.3.3.7 Jaccard相似係數最大 93
3.3.3.8 修訂版Jaccard相似係數最大 95
3.4 訂單批次選取問題 102
3.4.1 最小漸增權重懲罰值法 104
3.5 揀貨區域拜訪順序問題 106
3.5.1 動態揀貨區域拜訪順序法 107
3.5.2 鄰近揀貨區域優先演算法 109
3.5.3 模擬退火演算法 109
3.5.4 模擬退火演算法設置 111
第四章模擬實驗與分析 112
4.1 模擬實驗設計 112
4.1.1 揀貨環境設定 112
4.1.2 實驗訂單設定 114
4.1.3 揀貨環境假設 114
4.1.4 實驗因子組合 115
4.2 績效評估指標 117
4.3 統計分析 117
4.3.1 分析說明 118
4.3.2 依「揀貨系統總執行時間（TST）」為績效評估指標 118
4.3.2.1 個別因子之說明（依TST績效值） 119
4.3.2.2 不同因子交互作用之說明（依TST績效值） 122
4.3.2.3 最佳因子組合與績效（依TST績效值） 130
4.3.3 依「揀貨員總揀貨距離（TTD）」為績效評估指標 134
4.3.3.1. 個別因子之說明（依TTD績效值） 135
4.3.3.2. 不同因子交互作用之說明（依TTD績效值） 138
4.3.3.3. 最佳因子組合與績效（依TTD績效值） 146
4.3.4 依「揀貨員總忙碌時間（TBT）」為績效評估指標 150
4.3.4.1 個別因子之說明（依TBT績效值） 151
4.3.4.2 不同因子交互作用之說明（依TBT績效值） 154
4.3.4.3 最佳因子組合與績效（依TBT績效值） 162
4.4 實驗結論 166
第五章研究結論與建議 168
5.1 研究結論 168
5.2 未來研究建議 170
第六章參考文獻 171
中文文獻 171
英文文獻 172

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指導教授

何應欽(Ying-Chin Ho)

審核日期

2022-7-21

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