本研究整合固定路線鐵路客運列車停站方式與營運計畫之關係，以營運者營運成本最小化及旅客停站損失時間最小化為目標，構建模糊多目標鐵路客運最適停站模式。為提高模式求解效率，乃應用具有補償性之模糊總計函數，發展啟發式求解方法來求解，同時也以啟發式求解法來估算營運成本下限值。並以固定路線之高速鐵路為例，來驗證本方法之可用性及有效性。結果顯示，所求得的營運成本下限值與最小營運成本的差異程度約為1.4 ％以內；而所求得營運班次下限值及系統所需列車數下限值，與所求得的最佳解非常接近，顯示所構建之啟發式求解方法頗具實用價值。 This research develops a fuzzy multiobjective optimal model for train stopping scheduling which integrates the train stopping schedule and the operations plan. The objectives of the model are the operator's operating costs, and the user's travel time loss. To make the model solved efficiently, this research develops heuristic algorithms by using a compensatory fuzzy sets aggregation operator to obtain the optimal solution and the lower bounds for the objective. The empirical research is conducted for the high speed rail system. The difference between the lower bounds of operating costs estimated by the heuristic algorithms and that of the optimal solution is less than 1.4.%. The lower bounds of frequency and vehicle fleets obtained by the heuristic algorithms are closed to the optimal solution. The results indicate that the heuristic algorithms have practical advantages.
