中山管理評論  1994/6
第2卷第2期 p.1-17
Energy Research Group and Institute of Traffic and Transportation National Chiao Tung University
都市交通日益惡化,其解決之道端賴大眾運輸系統的普及化。但首先,必須有一套評估運輸系統績效的制度。本文即是針對公車系統績效建立完整、客觀且較簡便的評估程序。內容包括績效評估指標的選取、利用AHP 法求取指標的權重、加入模糊多屬性(FMADM) 的觀念在進行系統間的排序等三個部份。 本文以供給面(公車業者)、需求面(乘客)與監督面(政策)等三個方向來構建績效評估指標的選取架構,並從中選取16個評估指標;其次,應用AHP法的層級概念與特徵向量,收集決策群體(公車業者、乘客、交通主管單位、專家學者)的意見後,計算得到各指標的權重;最後,結合模糊多屬性決策中優勢排序(Outranking)的方法-TOPSIS對各公車系統進行評估與排序。本文並以台北市十家聯營公車為例,應用此評估程序進行系統間的排序。結果證明,此法不僅簡化了模糊概念引進後的複雜度,亦較符合公車系統績效評估的問題特性。
(633621944688437500.pdf 37KB)公車系統績效、績效評估指標、層級分析法、模糊多屬性決策
Recently, urban traffic has become worse and worse in Taipei city. The solution has to depend on universalization of public transportation. But, we need first a performance method for evaluating transportation systems. This paper focuses on establishing an objective and easier evaluation process. The selection of performance evaluation included the weight of indices, by using the AHP method and the priority rankings of all bus systems according to the concept of fuzzy MADM. In this paper the hierarchical structure of bus performance evaluation indices was constructed by considering the three aspects of supply side(bus firms), demand side(passengers) and supervisory side (policy). Then sixteen evaluation indices were selected in this hierarchical structure. We made use of the hierarchy concepts of the AHP method and its eigenvector from decision groups of bus operators, passengers, government authorities and scholar experts to caculate and obtain the weight of each indicator. Finally, the priority rankings of all bus systems-TOPSIS,were ranked by applying the outranking of fuzzy MADM. Finally, we illustrated and ranked ten bus firms in Taipei city by using the evaluation process established here. It was shown that simplification of the complexity of fuzzy application to bus system evaluation was more suited to the characteristics of these types of problems.
(633621944688437500.pdf 37KB)Bus System Performance, Performance Evaluation Indices, Analytic Hierarchy & Process(AHP), Fuzzy Multiple Attibute Decision Making.