|摘要: ||運輸計畫規劃（transportation programming）是運輸部門進行運輸計畫選擇之過程，包括計畫評估、選擇、排程與預算組合，以決策核定之運輸計畫集合。過去相關運輸計畫規劃問題較無計畫組合與綜效之考量，因此，導入計畫組合管理概念，考慮計畫組合之利益、成本與風險，建構計畫組合規劃模式，進行最適計畫組合方案之選擇，即成為重要之研究議題。本研究計畫組合規劃模式以計畫組合為決策對象，有別於過去計畫規劃問題以個別計畫為規劃對象，並考慮計畫組合之利益、風險及預算之不確定性，建構灰色多目標0-1整數規劃問題，並應用灰色理想解相似度順序偏好法（technique for order preference by similarity to ideal solution, TOPSIS）求解多目標計畫組合規劃模式之妥協解。本研究以行政院公共工程委員會之大型運輸建設計畫，作為實務數值範例應用問題之假設基礎，透過數值範例應用分析，驗證本研究模式之可行性。藉由不同目標式權重組合下，計畫組合規劃妥協解決策空間可顯示兩目標之間的權衡取捨率。而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模式之基礎；整合灰數於規劃模式中，即允許利益、風險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 is the process of selecting and determining a final set of transportation projects, including project evaluation, selection, scheduling and budget portfolio management. Since conventional transportation programming models lacked the consideration for project portfolios and synthetic effects, such important research topics arise as the introduction of a project portfolio management concept, the consideration for benefits, costs and risks of the project portfolios, the establishment of a project portfolio programming model, and the selection of optimum project portfolio solutions. This study developed a project portfolio programming model with project portfolios as the target for decision making rather than individual projects in the previous programming models. Since the programming tasks are filled with uncertainties in terms of benefits, risks and budgets of project portfolios, grey multiobjective 0-1 integer programming problems were designed. Additionally, a grey Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach was developed to solve the proposed model. With the large-scale transportation development projects of the Public Construction Commission, Executive Yuan, as the assumption basis of numerical examples and applications, the analysis confirmed the feasibility of the proposed model. The trade-off ratios between two goals were shown using different goal weight combinations for negotiations and decision making in regard to project portfolio programming. The proposed model uses project portfolios as the target for decision making, and can therefore set up a foundation for transportation programming models using a project portfolio management approach. The incorporation of grey numbers in the programming model allows possible ranges for the input values of benefits, risks and budgets, which helps to maintain the flexibility in decision making when planners are faced with and dealing with indefinite conditions for programming.