航空公司可以將飛機上同一艙等的相同座位以不同的價格販賣給顧客。由於每位顧客對於價格的接受程度不同，航空公司會根據需求預測，將顧客區分為數種費率等級；費率等級越高的顧客，表示其消費金額比其他費率等級顧客高。當有顧客來到時，決策者必須立即決定是否要滿足該顧客的訂位需求。為了增加飛機的收益，決策者會傾向拒絕部分低費率等級的顧客訂位需求並且保留座位給較高費率等級的顧客。
本論文考慮一個將顧客區分為多種等級的單一航班問題。顧客來到服從非同質性的卜瓦松過程；決策者的目標是最大化該航班的收益。本論文提出了兩種方法針對每一位來到顧客的訂位需求進行滿足與否其需求之即時判斷，此兩種方法分別是動態座位配給決策步驟(dynamic seat rationing decision procedure)以及期望收益價差決策步驟(expected revenue gap decision procedure)。根據模擬實驗的結果得知，期望收益價差方法相較於先前的研究方法而言，獲取的平均收益為最大，並且在不同的實驗條件下，期望收益價差方法皆有非常穩定的表現；同時，期望收益價差方法能夠在非常短的時間內，答覆顧客的訂位需求。

For the airline business, airliners are allowed to sell the seats of a same cabin for different prices. Normally, they allocate the seats of a cabin class into a number of the discrete fare classes based on the demand forecast of customers with different acceptable prices. A customer with demand in a higher fare class is willing to pay more. Each time when a customer with a fare class arrives, an airliner must decide whether to fulfill or reject the request immediately. In order to increase the revenue, the airliner may want to reject certain lower fare class customer requests and reserve the seats for future higher fare class customers.
The problem this study focuses on is rationing decision for a single-leg flight with multiple fare classes and the customer arrival process of an individual class is non-homogeneous Poisson. The objective is to maximize the revenue of a flight. This study develop two real-time decision procedures, dynamic seat rationing (DSR) and expected revenue gap (ERG) to help the airliner make a decision when a customer arrives. The simulation results show that ERG approach perform best among all test approaches and is very robust under various problem conditions. Also, it takes a very short computation time to execute on computer.

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