本研究之目的在於判定影響每一航班飛航安全之重要因素，並提供其調整方式，作為航空公司飛航簽派人員進行重新派遣作業時之參考。本研究以個案航空公司建置之飛航作業風險評估系統為基礎，該系統會在每一航班起飛前2小時，就派遣內容評估其風險值。當風險值過高時，應進行派遣內容調整以避免可能之安全性問題。本研究之作法是以一安全範圍內之風險值為目標，然後搜尋最小幅度之派遣內容修改，以期達到目標風險值。該航空公司之飛航作業風險評估系統乃以模糊推論系統為核心，因此本研究所發展之搜尋演算法亦以模糊規則之因果架構逆推可能之派遣內容組合。為了驗證本演算法之效能，本研究以該航空公司實際之飛行派遣資料進行實驗，並比較本演算法與遺傳演算法兩者之建議與原始派遣所衍生之風險值間的差異。 This study presents a decision support tool to identify the critical risk factors of a flight in advance, and to suggest adjustments of such factors for the dispatcher to reduce the flight’s risk. The case study airline has established a Flight Operation Risk Assessment System (FORAS) to evaluate the risk of a flight two hours before its departure; nevertheless, the function of critical risk factor identification and its corresponding adjustment suggestion is absent in the system. The present study proposes a search algorithm that is based on FORAS and its fuzzy reasoning mechanism to carry out the function of critical risk factor identification and adjustment suggestion. The algorithm is triggered when the risk of a flight is beyond the warning line. A target risk value in the safety zone is given, and the algorithm traces backward along the fuzzy rules in FORAS and finds the critical factors and the required changes of these factors to meet the target risk value. To justify the performance of the proposed algorithm, the real flight data from the case study airline are used, and the results are compared with that by a genetic algorithm.
