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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/74345

    Title: 灰色多目標計畫組合規劃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: 2011-12-28 18:24:06 (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。
    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:[Graduate Institute & Department of Transportation Management] Thesis

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