臺灣博碩士論文加值系統

宅配與快遞物流業者於都會區內發展機車快遞服務，提供高便利性、高時效性與戶對戶之服務，以因應B2C和C2C之消費型式，而隨著全球環保意識高漲，在政府積極推廣低碳運具使用下，物流業者逐漸嘗試建立綠能車隊，採用電動機車進行配送工作。然而，目前實務上多數機車快遞業者在進行車輛作業規劃時，仍仰賴快遞員之配送經驗，採用人工指派之方式，但此方法較費時、費力，且當業者採用電動機車執行配送任務時，須額外考量車輛之行駛里程限制以及補充電量問題，若仍透過人工指派方式將更為複雜及困難，且無法求得最佳化規劃結果。
因此，本研究針對機車專件快遞服務，即快遞員至需求之指定地點取貨後，直接送往指定配送地點之服務型式，從機車快遞服務業者之立場，利用時空網路流動技巧，以最小化總營運成本為目標，考慮電動車輛剩餘電量、充電站位置等限制條件，建構一電動機車快遞服務車輛排程模式。而由於本研究所建構之模式屬於整數多商品網路流量問題，為了提高求解大規模範例時之效率，研究以問題分解技巧為基礎之啟發式解法，搭配Gurobi最佳化軟體進行求解，並參考國內某機車快遞業者之訂單資料，設計不同情境之範例，以測試模式與啟發式解法之實用性。測驗結果得知，利用啟發式解法對不同情境之範例進行求解，皆能於30分鐘內求得和Gurobi軟體得到之下限解差距在8%內之啟發解，顯示本研究之模式與啟發式解法能有效應用於實務上。研究結果可提供機車快遞服務業者作為未來採用電動機車進行專件配送時之參考。

In response to B2C and C2C business models, courier service providers adopt scooters for express delivery service in metropolitan areas, which increases convenience and timeliness for delivery. Besides, along with the growth of environmental awareness, the government actively promote low-carbon transport, which makes courier service providers gradually replace petroleum motorcycles with electric scooters to achieve green logistics. However, courier services providers will need to consider vehicle mileage range and the location of charging stations when planning the routing of a fleet of e-scooters. Therefore, the study addresses the optimization problem of scheduling a fleet of e-scooters that are assigned for paired pickup and delivery services. The study proposes an optimization model which is developed based on the time-space network. The objective is to minimize service providers’ total operating cost subject to a set of operating constraints for e-scooters. The model is formulated as an integer multiple-commodity network flow problem, which is characterized as NP-hard. Hence, the study develops a decomposition-based heuristic, with the assistance of the mathematical problem solver, Gurobi, to efficiently solve the problem with practical sizes. Test instances are generated based on the data provided by a Taiwan courier service provider, in order to evaluate the efficiency and effectiveness of the proposed model and the heuristic algorithm. The result shows that the heuristic algorithm takes within 30 minutes to complete the solution process. In addition, the gaps between heuristic solutions and lower bounds that are obtained by Gurobi are less than 8%. As a result, it is shown that the proposed model and heuristic algorithm are effective planning tools for scheduling a fleet of e-scooters that are appointed for paired pickup and delivery services.

摘要 i
Abstract ii
致謝 iii
目錄 iv
表目錄 vi
圖目錄 vii
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 2
1.4 研究方法與流程 3
第二章 文獻回顧 5
2.1 城市物流 5
2.2 宅配業與快遞業現況 7
2.2.1 宅配業與快遞業之比較 7
2.2.2 機車宅配與快遞業現況 8
2.3 綠色車輛配送相關文獻 10
2.4 車輛途程問題相關文獻 11
2.4.1 車輛途程問題 11
2.4.2 替代能源車輛途程問題 12
2.4.3 電動車輛途程問題 13
2.5 時空網路相關文獻 17
2.6 小結 20
第三章 模式建構 22
3.1 問題描述 22
3.1.1 假設條件 23
3.1.2 配送需求時空網路 24
3.2 電動機車時空網路 24
3.3 電動機車快遞服務車輛排程模式 28
3.4 小範例測試 30
3.4.1 參數設定 30
3.4.2 小範例測試結果 31
3.5 啟發式解法 33
第四章 範例測試 37
4.1 範例設計 37
4.1.1 配送路網規劃 37
4.1.2 電動機車相關參數設定 37
4.1.3 配送需求設定 39
4.1.4 模式輸出資料與環境設定 39
4.2 範例測驗結果 40
4.2.1 啟發式解法求解效果 40
4.2.2 情境一求解結果 43
4.2.3 情境二求解結果 44
4.2.4 情境三求解結果 45
4.3 敏感度分析 46
4.3.1 訂單量 47
4.3.2 車輛續航里程 48
4.3.3 發車成本 49
第五章 結論與建議 50
5.1 結論 50
5.2 未來研究方向與建議 51
參考文獻 52

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