臺灣博碩士論文加值系統

配送到手(Attended home delivery)是指網路商店為顧客提供送貨上門的宅配服務中的一種特別服務。在這項服務中，物流士會在指定的配送時段將客戶訂購的商品配送到指定地址，而特別的是，為了保證商品的安全性或新鮮度等，配送地點必須有人在家進行簽收。
提供生鮮蔬果的網絡商店在進行配送到手服務時，會與顧客確定一個較窄的配送時段，而在實際運作中，發現顧客傾向選擇相同的配送時段。因此，該網絡商店為了滿足尖峰時段的顧客訂單，必須投入較多的車隊資源，將生鮮蔬果從倉庫配送到地理位置分散的顧客位址。其次，由於有限的機車承載容量和生鮮蔬果保冷時長，在進行配送到手服務時，物流士在其每天的工作時間內通常需要多趟次地回到倉庫裝載之後需要服務的顧客包裹。最後，由於顧客不在家而導致的配送失敗，迫使物流士必須對這部分顧客進行再配送，從而顯著增加了物流成本。
因此，本研究旨在通過整合誘因策略和時窗設計的方法來幫助提供生鮮蔬果的網絡商店優化其在進行配送到手服務時所遇到的上述三個問題。構建了基於兩階段隨機規劃的考慮了隨機不在家顧客的帶時間窗的多趟次車輛路徑問題的數學模型，並預期利用基於Dantzig-Wolfe Decomposition的演算法求解實例案例。

Attended home delivery is commonly asked service by online grocery shopping customers. The service delivers ordered goods to the customers at appointed service time windows during which the consumers should be present for the delivery. In practice, the customers impose quite similar delivery time windows. Hence, the online grocer needs to dispatch a large fleet of couriers from its depot to service geographically scattered customers. Furthermore, a courier usually needs to run multiple trips to provide attended home delivery within its working hours per day due to limited trip duration and carrying capacity. Moreover, failed deliveries due to unattended customers force couriers to make second delivery and thus significantly increase logistics cost. Therefore, this research intends to help the online grocer optimize its attended multiple home deliveries by integrating incentive schemes and time-slot designs to overcome the aforementioned operating challenges.

摘要......i
Abstract......ii
誌謝......iii
目錄......iv
表目錄......vi
圖目錄......viii
一、緒論......1
1.1 研究背景......1
1.2 研究內容和方法......5
1.3 研究架構......7
二、 配送到手相關文獻回顧......9
2.1 配送時段設計......9
2.2 網購消費者行為......10
2.3 路線規劃策略......11
2.4 配送到手相關文獻小結......14
三、網購消費者不在家率分析......16
3.1 研究方法概述......16
3.2 資料來源與描述......21
3.3 群集分析......23
3.4 貝氏分析......26
四、時窗設計與誘因策略......35
五、多次配送車輛路徑規劃數學模型......40
5.1 問題描述......40
5.2 集合、參數與變數設定......43
5.3 數學模型......46
六、求解演算法......52
6.1 Dantzig-Wolfe 分解法......52
6.2 時窗方案指派問題求解演算法......58
6.2.1 時窗方案指派問題數學模型調整......58
6.2.2 時窗方案指派問題求解演算法設計......60
6.3 考慮隨機不在家顧客的帶時間窗的多趟次車輛路徑問題求解演算法......70
6.3.1 求解Two-Stage MTVRPTWSC主架構......74
6.3.2 混合基因演算法求解MTVRPTWs 算法說明......76
6.3.3 插入法......80
七、實例測試與結果分析......81
7.1 實例數據描述......81
7.2 隨機情境產生......83
7.3 測試結果分析......91
7.3.1 範例測試......91
7.3.2 小案例測試與規模較大的實例測試結果分析......97
八、結論......102
參考文獻......103
附錄A 演算法虛擬碼......107
附錄B 實例測試之顧客資料......109
附錄C 問卷調查......141

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