風險考量下之機位保留最佳化規劃

The Optimal Planning for Airlines Reservation

曹展熙(Chan-Hsi Tsao)

指導教授 ： 邱昭彰

元智大學/資訊學院/資訊管理學系/碩士(2004年)

摘要

在競爭激烈與複雜的產業環境中，如何有效的運用收益管理之方法，而使企業獲取最大之利潤，一直是業者與學術界所關注的議題。以航空業為例，諸如業者間訂價可調整之情況、行銷活動的採用、各艙等機位的需求數、旅客之不出席、超賣機位賠償等，均為影響航空旅運業者收益管理之重要因素。
本研究將以國內某兩航空公司之特定航班為研究標的。並預測在單一與多重艙等之情況下，當企業是否進行票價之調整，與決策是否考量風險下，所可獲得之利潤與保留位水準。
所建構之航空公司收益管理獲利模式中，將考量不同之風險因素，以有效反映實際經營情況。並配合蒙地卡羅模擬與基因演算法所結合之方法，以協助求取各艙等在風險考量下之最佳保留位策略，與預期之平均利潤。本研究之結果，實際上可成為制定機位保留最佳化策略之前置規劃的基礎與輔助。

關鍵字

收益管理 ； 機票訂價 ； 機位保留 ； 蒙地卡羅模擬 ； 基因演算法

並列摘要

In the competitive and complex industrial environment, how to use the yield management methods effectively make business gain the maximum profit is an interested issue to managers and scholars all the time. In the airline industry, for instance, all the important factors such as pricing adjustable status between competitors, marketing activities, seats demand of each fare class, the no-shows rate of customers and the compensation for overselling can affect the yield management of airlines.
In this study, the research targets are specific flights of two domestic airlines. We will also forecast the profit and the level of reservation of seats whether the business adjusts the price and considers the risks or not under single or multi fare class situations.
When we build the profit model of yield management for airlines, the model will consider the risk factors to reflect with the real operative situation effectively. Using the novel method which combines Monte Carlo simulation with genetic algorithms, help us find out the optimal reservation strategy of airline’s seats with risks for each fare class and the expectable mean profit. The experimental results in this research can be a foundation and assistance of pre-implement planning of reservation strategy of airline’s seats in practice.

並列關鍵字

Yield Management ； Pricing ； Airline Seat Reservation ； Monte Carlo Simulation ； Genetic Algorithms

參考文獻

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