本研究主要目的是建構一鐵路列車超額訂位之收益管理模式，以此模式探討在臺灣高鐵列車乘客不同之隨機到站型態下，使用不同列車超額訂位策略之收益分析。在此超額訂位模式中，應用在於旅客需求與列車座位相差不大之情形，其模式主要考量因素是高鐵乘客到站與否之隨機性，利用二元變數來建構高鐵乘客情境收益式與補償、賠償成本式。本研究使用蒙地卡羅模擬法來處理隨機性之變數，透過模擬探討不同超額訂位策略對於列車收益之影響。本研究亦利用敏感度分析探討在不同乘客未到率下，列車收益最大之超額訂位率。此外，本研究亦推估出列車收益最大前提下之最適高鐵列車指定席與自由席之車廂分配比例。研究結果顯示：在乘客未到率為 10%~20%之情境假設下，高鐵最適超額訂位率為估計乘客未到率再加 5%時之列車收益最佳。至於列車最適之指定席與自由席車廂分配比例，在乘客未到率小於 10%時，最適分配比例為 8:3；在估計乘客未到率為10%~20%時，最適分配比例可為 10:1。

The study aims to establish a railway over-booking yield management model. A binary function is utilized to formulate a high-speed railway formula consisting of benefit, compensation and discount cost. By focusing on the random distribution of high-speed railway passenger’s arrivals and absences, the Monte Carlo method is applied to compute random variables and calculate 1,000 random variations of the HSR over-booking model. Outcome of calculations is normally distributed and the effects of over-booking on railways are analyzed. Sensitivity analysis on different models is conducted to identify the best overbooking strategy and optimal coach distribution of reserved seats and unreserved seats. Results assume a 10%-20% no-show rate while the most reasonable no-show rate is 5%, which closely represents that of the high-speed railway. The optimal coach distribution of reserved seats and unreserved seats is 8:3 when the no-show rate is less than 10%. When the no-show rate is between 10%~20%, the best care distribution is 10:1.