城際客運鐵路之列車停站與列車服務計畫決策支援系統──以臺灣高鐵為例

A DECISION SUPPORT SYSTEM FOR OPTIMIZING RAILWAY STOPPING PATTERNS AND TRAIN SERVICE PLAN - APPLICATION TO THE TAIWAN HIGH SPEED RAIL

城際客運鐵路業者為滿足不同旅客之需求，通常會規劃每站皆停、越站停車或直達快車之產品組合，再擬定每小時各停站型態之發車頻率來提供服務。由於停站型態組合與發車頻率，通常是業者依據經驗法則或在部分民意需求下妥協的產品，除了無法顧及整體之最佳化安排外，亦甚少考量列車與旅次之時空遞移現象。基於上述原因，本研究致力發展一決策支援系統，以最小車內旅行時間找出最佳的停站型態組合，再以業者最大利潤為目標進行列車服務計畫求解。作者延續過去的研究成果，將停站模式精進為可求解大規模的0-1整數規劃問題，之後再將停站型態組合的輸出作為列車服務計畫的輸入，並納入旅次起迄之時空遞移現象，利用混合整數規劃找出不同時段下各停站型態的列車頻率。本研究並將所構建之模式應用在臺灣高鐵，在此案例分析中顯示，該決策支援系統可正確且有效率地找出最佳停站型態組合與列車服務頻率，而旅客車內旅行時間與業者利潤均有更好的績效表現，顯見本決策支援系統不但能滿足旅客需求，亦能協助業者創造更多利基。

To satisfy different needs of passengers, intercity railway operators usually design various stopping patterns, such as all-stop, skip-stop, and express trains. The operators then assign adequate hourly service frequency for each stopping pattern. Since stopping patterns and service frequencies are typically determined by empirical rules or needs of some local citizens, the resulting arrangements may not be optimal and comprehensive, and most of them do not consider the time-space transition of trains and trips. Thus, this research aims to develop a decision support system to generate the optimal combination of stopping patterns for minimizing passenger in-vehicle time, and to obtain the best train service plans for maximizing operators’ profit. We refined the previous model for stopping pattern planning to resolve large-scale 0-1 integer programming problems. The optimal combination of stopping patterns obtained was then input to a train service plan, and the time-space transitions from the beginning to the end of trips were included, to determine the service frequencies of each stopping pattern in different periods through mixed integer programming. The proposed models were applied to the Taiwan High Speed Rail. The case analysis showed that the decision support system could precisely and efficiently find the optimal stopping patterns and service frequencies; the resulting passenger in-vehicle time and operators’ profit exhibited better results than current practices. The results demonstrate that the decision support system can not only meet passengers’ needs but also help operators to create more profits.