計程車共乘及旅客配對整合模式暨求解演算法之研究

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陳信諺(Hsin-yein Chen) 查詢紙本館藏

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土木工程學系

論文名稱

計程車共乘及旅客配對整合模式暨求解演算法之研究
(Integrated Matching Models and Solution Algorithms for Taxipool.)

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摘要(中)

近年來台灣都會區交通量的成長迅速，計程車之使用亦日益普遍，如何有效的透過共乘以提高計程車之服務能量，則成為一重要之課題。然而，目前計程車行在計程車共乘的配對上，多採用人工經驗排班方式，不僅費時且難以得到最佳之配對結果，而降低共乘之績效。緣此，吳權哲(2007)提出一架構，含三個模式，以分段方式求解多起迄需求計程車共乘配對問題，然此種求解方式並未以整體系統最佳化觀點考量，故未能求得一系統化之最佳解。為更有效幫助業者求得一系統化之最佳解，本研究構建一符合現況之多起迄需求計程車共乘配對整合模式，以期幫助業者規劃一良好之共乘配對方式，進而提升營運績效。
本研究針對多起迄對之預約式旅次，以共乘配對系統規劃者的角度，發展一系統化之最佳化模式。此模式預期可定式為一整數多重網路流動問題，屬NP-hard問題，當問題規模變大時，可能難以在有限的時間內利用數學規劃軟體求得一最佳解。緣此，本研究針對此模式發展一系列以貪婪式演算法為基礎並結合巨集式啟發解法之混合式(hybrid)求解演算法，以求解計程車共乘配對問題。最後，本研究以臺北市一計程車行之營運資料為範例進行測試與分析，結果甚佳，顯示本研究所建構之模式與求解之演算法，應可為未來計程車進行實務共乘配對之參考。

摘要(英)

In recent years, the traffic volume has grown significantly and taxi becomes more popular than before in Taiwan. How to improve the service performance effectively by using taxipool becomes an important issue. However, currently most taxi carriers use a trial-and-error process for taxipool matching, which is neither effective nor efficient. Wu (2007) developed a taxipool matching framework, including three models, and the framework had been solved by using decomposition method, without optimization from a systemic perspective. Therefore, we develop a system optimization multiple OD matching model to help the taxi carriers to solve a better solution from systemic perspective. It is expected that such model is useful tool for the taxi carriers to plan the most suitable passenger matching and fleet scheduling.
We construct an integrated model focusing on advanced-order passenger trips from the planner perspective. The model is formulated as integer multiple commodity network flow problems, which is characterized as NP-hard. Since the problem size is expected to be huge, the model is more difficult to solve in a reasonable time. Therefore, we also try to develop a family of hybrid solution algorithms, based on Greedy Algorithm and Meta-heuristics, for solving passenger matching and fleet scheduling problems. Numerical tests based on real operating data from a taxi carrier are performed to evaluate the proposed solution algorithm. The preliminary results are good, showing that the model and the algorithms could be useful for passenger matching and fleet scheduling.

關鍵字(中)

★ 貪婪式演算法
★ 啟發解
★ 計程車共乘
★ 多重貨物網路流動問題
★ 巨集式啟發解法

關鍵字(英)

★ Meta-heuristics
★ Heuristic
★ Greedy Algorithm
★ Taxipool
★ Multiple commodity network flow problem

論文目次

摘要 I
ABSTRACT II
誌謝 III
目錄 IV
圖目錄 VI
表目錄 VII
第一章緒論 1
1.2 研究目的與範圍 2
1.3 研究方法與流程 3
第二章計程車共乘現況概述與文獻回顧 4
2.1 國內外計程車共乘現況 4
2.2 共乘及撥召的相關文獻 5
2.3 時空網路的相關文獻 10
2.4 啟發式演算法的相關文獻 13
2.5 文獻評析 16
第三章模式構建 18
3.1 共乘配對模式 18
3.1.1 模式基本假設 18
3.1.2 時空網路 20
3.1.2.1 車流時空網路 20
3.1.2.2 人流時空網路 22
3.1.3 模式符號說明 24
3.1.4 數學定式 27
3.3 小結 27
第四章求解演算法設計 29
4.1 初始解 30
4.2 改善解 33
4.2.1 Heuristic(H1) 33
4.2.2 Heuristic結合TA(H2) 35
4.2.3 Heuristic結合GDA(H3 36
4.3 下限解 37
4.4 小結 41
第五章範例測試 42
5.1 輸入資料 42
5.1.1 車隊規劃資料 42
5.1.2 共乘旅次資料 43
5.2 模式發展 44
5.2.1 問題規模 44
5.2.2 模式輸入資料 44
5.3 電腦演算環境及設定 45
5.3.1 電腦演算環境 45
5.3.2 相關參數設定 45
5.3.3 模式輸出資料 47
5.4 測試結果與分析 47
5.5 敏感度分析 50
5.5.1 單一車輛規劃車容量之敏感度分析 50
5.5.2 乘客旅行時間價值成本之敏感度分析 51
5.6 方案分析 53
5.6.1 配對組織之立場分析 53
5.6.2 系統服務人數及派車數分析 55
5.6.3 初始解法之參數設定分析 57
5.7 演算法求解績效分析 58
5.8 小結 60
第六章結論與建議 61
6.1 結論 61
6.2 建議 62
6.3 貢獻 62
參考文獻 64
附錄 71
附錄一 CPLEX Callable Library Code 71
附錄二範例測試之輸入資料 72
附錄三測試範例求解結果 74

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指導教授

顏上堯(Shangyao Yan)

審核日期

2008-7-23

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