類Locusbots系統之揀貨區域的AGV選取問題與派車問題研究

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吳羿辰(Yi-Chen Wu) 查詢紙本館藏

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類Locusbots系統之揀貨區域的AGV選取問題與派車問題研究

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摘要(中)

近年來資訊科技迅速發展，再加上行動網絡的普及化，造成電子商務的盛行，因此市場需求逐漸轉變為「少量、多樣化」，市場需求的改變同時也提升了物流中心的作業難度，其中對於揀貨作業更甚明顯。根據 De Koster et al.（2007）的研究指出，目前大多數的物流中心仍屬於勞力密集的產業，揀貨作業不僅相當耗費成本，更是一種屬於勞力密集的活動，在物流中心裡與揀貨作業相關的人力佔了50%以上。為了因應「少量、多樣化」需求的時代來臨，適時地導入自動化設備並規劃一個合適的揀貨策略，將對物流中心的成本、產能以及效率有著決定性的影響。

由於類 Locusbots 系統可以任意增加或減少無人搬運車的數目，因此可以有效地解決訂單淡、旺季的問題。除此之外 Locusbots 可以利用動態路徑規劃，即時更新揀貨環境狀態，有效避開路上各種障礙物，並規劃最有利的揀貨路徑。同時在類 Locusbots 系統，揀貨員不必在物流中心裡四處走動，其只需固定待在揀貨區域裡，無人搬運車會載送訂單及揀貨箱至揀貨區域讓揀貨員進行揀貨作業，如此一來不僅可以降低人力成本，同時可以提升揀貨作業之效率與準確性。

基於上述原因，本研究將針對類 Locusbots 系統中的揀貨策略進行探討，以「揀貨區域選擇 AGV 問題」以及「派車問題」進行研究，最後利用 Arena 模擬軟體實驗之結果，分析本研究提出的數種法則在不同績效指標下的表現，期望可以找出最合適的揀貨策略組合，並對未來之類似研究有相對貢獻。

摘要(英)

Nowadays, the rapid development of information technology and popularization of mobile networks has led to the prevalence of e-commerce, the market demand has gradually changed to "small and diverse", the change in market demand has also increase the difficulty of logistics centre operations, it’s even more obvious for picking operations. According to the research of De Koster et al. (2007), most logistics centres are still labor-intensive industries, picking operations are not only cost-intensive but also a labor-intensive activity, picking operation-related manpower accounted for more than 50% in the logistics centres. In order to cope with the advent of the era of "small and diverse" demand, introduction of automation equipment timely and planning a suitable picking strategy will have a decisive impact on the cost, production capacity and efficiency of the logistics centres.

Since the Locusbots system can arbitrarily increase or decrease the number of Locusbots, so can effectively solve the problem of weak and peak seasons. Locusbots can use dynamic path planning which can update environment information to avoid obstacles effectively and plan the picking path smoother. In the Locusbots system, the pickers don’t need to walk around in the logistics centre, pickers only need to stay in the picking zone, and the Locusbots will carry the order and the picking boxes to the picking zone. In this way not only reduce labor costs but also improve the efficiency and accuracy of picking operations.

Base on the above reasons, the research will mainly discusses the Locusbots system with "selecting AGV in the picking zone problem" and "dispatching problem". Finally, use the results of Arena simulation software experiments, analyze the performance of the several rules proposed in this research under different performance indicators, hoping to find the most suitable combination of picking strategies and make a relative contribution to similar research will be made in the future.

關鍵字(中)

★ 物流中心
★ Locusbots系統
★ 訂單選取法則
★ 揀貨區域選擇AGV法則
★ 派車法則

關鍵字(英)

★ Distribution Centre
★ Locusbots system
★ Order selection
★ Picking Zone Selecting AGV
★ Dispatching

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 3
1.5 論文架構 5
第二章文獻探討 8
2.1 Locusbots 系統（Locusbots System） 9
2.1.1 Locusbots系統環境與作業流程 10
2.1.2 Locusbots設備介紹 11
2.2 物流（Logistics） 15
2.2.1 物流的定義（Logistics definition） 15
2.2.2 物流中心介紹（Distribution centre introduction） 16
2.3 倉儲規劃（Warehouse planning） 18
2.3.1 倉儲設計（Warehouse design） 18
2.3.2 走道設計（Aisle design） 23
2.4 揀貨作業規劃（Picking operation planning） 27
2.4.1 揀貨方法（Picking method） 27
2.4.2 揀貨政策（Picking policy） 29
2.4.3 揀貨路徑策略（Picking routing strategy） 34
2.4.4 揀貨作業績效評估指標（Picking operation performance evaluation indicator） 39
2.5 AGV 派車法則（AGV dispatching rule） 40
2.5.1 單屬性派車法則（Single attribute dispatching rule） 40
2.5.2 多屬性派車法則（Multiple attribute dispatching rule） 44
第三章研究方法 46
3.1 Locusbots作業流程與問題分析 46
3.2 各研究問題之方法整理 48
3.3 研究問題說明 51
3.4 訂單選取問題 53
3.4.1 隨機選取法 53
3.5 派車問題（決定無人搬運車該至哪一個揀貨區域進行揀貨作業） 54
3.5.1 隨機派車法 54
3.5.2 最短旅行距離法 54
3.5.2.1 範例說明 54
3.5.3 最大揀貨品項數法 56
3.5.3.1 範例說明 56
3.5.4 最小揀貨品項數法 57
3.5.4.1 範例說明 57
3.5.5 最大（揀貨品項數 / 旅行距離）比例法 57
3.5.5.1 範例說明 58
3.5.6 最小（揀貨品項數 / 旅行距離）比例法 59
3.5.6.1 範例說明 60
3.5.7 最少剩餘揀貨時間法 61
3.5.7.1 範例說明 68
3.5.8 最早最晚可開始揀貨時間法 72
3.5.8.1 範例說明 79
3.5.9 多屬性派車法 84
3.6 揀貨區域選擇AGV問題（揀貨區域優先處理哪一台AGV） 87
3.6.1 隨機選擇法 87
3.6.2 最少剩餘揀貨區域數法 87
3.6.2.1 範例說明 87
3.6.3 最早到期時間法 88
3.6.3.1 範例說明 88
3.6.4 在該ZONE等候時間最久法 89
3.6.4.1 範例說明 89
3.6.5 最少寬鬆時間法 89
3.6.5.1範例說明 93
3.6.6 最少剩餘揀貨品項數法 96
3.6.6.1 範例說明 96
3.6.7 在系統停留時間最久法 97
3.6.7.1 範例說明 97
3.6.8 在該ZONE揀貨品項數最少法 98
3.6.8.1 範例說明 98
3.6.9 多屬性揀貨區域選擇AGV法 99
第四章模擬實驗與分析 102
4.1 模擬實驗設計 102
4.1.1 揀貨環境設定 102
4.1.2 實驗訂單設定 103
4.1.3 揀貨環境假設 104
4.1.4 績效評估指標 105
4.2 統計分析 105
4.2.1 分析說明 106
4.2.2 依「揀貨系統總執行時間（TST）」為績效評估指標 106
4.2.2.1 個別因子之說明（依TST績效值） 107
4.2.2.2 不同因子交互作用之說明（依TST績效值） 110
4.2.2.3 最佳因子組合與績效 120
4.2.3 依「訂單在系統內總時間（TTIS）」為績效評估指標 126
4.2.3.1 個別因子之說明（依TTIS績效值） 126
4.2.3.2 不同因子交互作用之說明（依TTIS績效值） 130
4.2.3.3 最佳因子組合與績效 140
4.3 實驗結論 147
第五章研究結論與建議 149
5.1 研究結論 149
5.2 未來研究建議 150
參考文獻 152
中文文獻 152
英文文獻 155

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指導教授

何應欽(Ying-Chin Ho)

審核日期

2023-7-14

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