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研究生: 周佰賢
Chou, Bo-Hsien
論文名稱: 考慮需求變化狀況及增設臨停區之公共自行車共享系統租借站分群與車輛調度策略研究
Site Clustering and Bike Repositioning Strategies for Public Bike Sharing Systems based on Demand Profile and Temporary Bike Buffer Zone
指導教授: 王逸琳
Wang, I-Lin
學位類別: 碩士
Master
系所名稱: 管理學院 - 工業與資訊管理學系
Department of Industrial and Information Management
論文出版年: 2015
畢業學年度: 103
語文別: 中文
論文頁數: 72
中文關鍵詞: 自行車共享系統租借站分群需求變動趨勢動態運補策略管理臨停區整數規劃
外文關鍵詞: Bike sharing system, Site clustering, Demand profile, Dynamic repositioning, Temporary bike buffer zone, Integer program
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  • 在公共自行車共享系統的營運期間,為了避免使用者無車可借或無位可還,營運者必須在各租借站間以運補車來回調度自行車以達到供需平衡,此即為動態運補策略管理問題,該問題與車輛途程問題文獻中的收送貨問題十分類似,通常必須使用作業研究理論的整數規劃法求解。由於整數規劃法經常耗時過久,本研究擬先由實際收集而得的歷史租還資料為基礎,利用分析而得的各租借站租還需求變動趨勢來簡化問題,依循先分群後規劃路線(Cluster-First Route-Second)的策略,第一階段提出「K-means分群演算法」與「預測趨勢之分群數學模式」等兩種分群方式來劃分出合宜的租借站分群,以劃分運補責任區域;第二階段再針對各責任區域依(1)無增設臨停區、(2)所有租借站皆增設臨停區、(3)臨停區選址等三種情境,提出能滿足最多租還需求的單一運補車運補數學模式,藉此規劃出每台運補車之最佳自行車調度策略以及暫時人力資源之最佳配置方式,以改善自行車共享系統的服務品質。數值測試結果顯示,利用各租借站租還需求變動趨勢來簡化問題的方式的確能有效地在短時間內求得幾近最佳的動態運補方式;此外,臨停區的設置的確能大幅改善服務品質,而本論文亦已針對現實系統中該如何以有限的資源設置合適的臨停區個數與位置提出整數規劃的數學模式,可供相關業者在後續實務營運時的臨停區選址決策參考依據。

    The public bike sharing system has become popular in many metropolitan areas worldwide, due to its contribution to the green transportation. This thesis focuses on more practical side of bike sharing system management. In particular, we first conduct big data analysis to learn the rental tendency pattern of demand profile for each rental site, and then use the tendency pattern as a key to simplify the procedures of site clustering and bike repositioning strategies. In our two stage strategy, we first give two methods to cluster rental sites, one by a modified K-means algorithm and the other by an integer program, and then we propose three dynamic repositioning models for each cluster managed by a single repositioning vehicle in the second stage. We also investigate the service quality improvement by installing a temporary bike buffer zone besides a rental site, based on the current practice of YouBike. To make it more realistic, we integrate the dynamic repositioning with a locational model to help decision maker to select suitable numbers and locations for installing temporary bike buffer zones. Based on the results of our computational experiments, by using the rental tendency pattern of demand profile, our proposed integer program models can calculate near optimal solutions within much shorter time, and makes the dynamic repositioning strategies feasible for large scale public bike sharing systems.

    目錄 摘要 I Abstract II 誌謝 VI 目錄 VII 圖目錄 X 表目錄 XII 第一章 緒論 1 1.1 研究背景 1 1.2 研究動機 3 1.3 研究目的 5 1.4 論文架構 7 第二章 文獻探討 8 2.1 自行車租借站系統運作之相關文獻 8 2.1.1 使用者行為 8 2.1.2 營運策略 9 2.2 運補車路徑之相關文獻 9 2.2.1 車輛途程問題 9 2.2.1.1 收送貨問題 10 2.2.1.2 兩階段式車輛途程問題 10 2.2.2 貨櫃調度問題 11 2.3自行車運補策略之相關文獻 12 2.3.1 靜態運補 12 2.3.2 動態運補 13 2.4 小結 17 第三章 自行車租借站分群之研究 18 3.1 K-means 分群演算法 18 3.2預測趨勢之分群數學模式 25 3.2.1 「需求趨勢相同的租借站」之運補相斥性 25 3.2.2 預測趨勢之整數規劃分群模式 26 3.2.2.1 研究方法與資料分析 26 3.2.2.2 參數與變數的定義 27 3.2.2.3 數學模式的建立 28 3.3 小結 29 第四章 自行車需求變化之運補策略研究 30 4.1 問題描述與假設 30 4.1.1 問題描述 30 4.1.2 問題假設 32 4.1.3 「需求趨勢相同的租借站」之運補相斥性 34 4.2 原始自行車租借站之運補模式 36 4.2.1 參數與變數的定義 36 4.2.2 數學模式的建立 37 4.3 增設臨停區與人力之運補模式 40 4.3.1 參數與變數的定義 41 4.3.2 數學模式的建立 42 4.4 臨停區選址之運補模式 45 4.4.1 參數與變數的定義 45 4.4.2 數學模式的建立 46 4.5 小結 48 第五章 實際範例與數值分析 49 5.1 測試情境 49 5.2 兩種不同自行車租借站分群方式之數值分析 52 5.3 「需求趨勢相同的租借站之運補相斥性」的影響之數值分析 54 5.4 三種不同自行車租借站運補模式之數值分析 57 5.5 小結 58 第六章 結論與未來研究方向 59 6.1 結論與貢獻 59 6.2 未來研究方向 61 參考文獻 63 附錄A、K-means分群結果 66

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