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    Title: 灰色多目標計畫組合模式於運輸計畫規劃之研究
    Other Titles: A Grey Multi-objective Project Portfolio Programming for Transportation Programming
    Authors: 牛紀芸;Niou, Ji-Yun
    Contributors: 淡江大學運輸管理學系碩士班
    溫裕弘;Wen, Yuh-Horng
    Keywords: 運輸計畫規劃;計畫組合管理;灰色多目標整數規劃;灰色TOPSIS;Transportation Programming;Project Portfolio Management;Grey Multi-objective;Project Portfolio Programming Model;Grey Numbers
    Date: 2011
    Issue Date: 2013-03-13 10:19:33 (UTC+8)
    Abstract: 運輸計畫規劃(Transportation programming)是運輸部門進行運輸建設計畫選擇之過程,包括計畫評估、選擇、排程與預算限制,以決策核定之運輸計畫集合。過去相關運輸計畫規劃問題大多假設互斥且獨立之計畫方案,較無計畫組合與綜效之考量,因此,導入計畫組合概念,建構計畫組合規劃模式,可同時考慮多重計畫組合下所衍生之綜效,進行最適計畫組合方案選擇,以滿足計畫組合決策目標並為整體社會得到最大利益,藉此完成政府投資計畫目的,即成為值得研究的議題。
    本研究整合灰數建構灰色多目標0-1整數規劃之計畫組合規劃模式,有別於過去計畫規劃問題以個別計畫為規劃對象,本研究計畫組合規劃係以計畫組合為決策對象,並考慮成本、利益以及預算之不確定性,建構灰色多目標0-1整數規劃問題,並應用灰色TOPSIS法求解多目標計畫組合規劃模式之妥協解。本研究以公共工程委員會之大型運輸建設計畫作為實務數值範例假設之基礎,透過數值範例分析驗證本研究模式之可行性;藉由不同目標式權重組合之計畫組合規劃妥協解決策空間可顯示,不同權重組合所代表之兩目標之間的權衡取捨率,亦即可提供較大之決策彈性。透過預算額度與灰色程度之敏感度分析,發現總預算改變對計畫組合規劃結果影響較為明顯,而灰色程度改變之規劃結果則堪稱強固。預算改變即會改變計畫組合結果,隨預算提高,較傾向組合計畫之規劃解。
    本研究計畫組合規劃模式係以計畫組合為決策對象,可作為以計畫組合管理進行運輸計畫規劃之規劃模式基礎;整合灰數於規劃模式中,即允許成本、利益及預算輸入值為大概範圍之區間值,有助於規劃者面對並處理不明確規劃條件下,維持規劃結果之變動決策彈性。
    Transportation programming, a process of selecting final sets of projects for funding given budget and other constraints, is becoming more complex as a result of new federal laws, local planning regulations, and increased public involvement. This study develops a grey multiobjective project portfolio programming model towards the problem of transportation programming. In contrast with other conventional transportation programming models, a mathematical programming model for choosing optimum portfolios of transportation projects is developed. Maximize the net present worth of project portfolios and the mean-variance criteria are taken into consideration. Since the programming tasks are filled with uncertainties, the parameters (costs, benefits, and budgets) and mean-variance of project period are all designed as grey numbers, which represented the possible ranges other than crisp values. Additionally, a grey TOPSIS approach for solving the proposed model is developed. Finally, a case study with a numerical example demonstrates the feasibility of applying the proposed models. Sensitivity analysis is also discussed. The results of this study verify that the models are practicable, and also provide higher flexibility on decision-making for transportation programming.
    Appears in Collections:[運輸管理學系暨研究所] 學位論文

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