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Solving airline overbooking problems using fuzzy knowledge-based optimisation

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  1. Tez No: 403268
  2. Yazar: BERKCAN UYAN
  3. Danışmanlar: Dr. AMMAR AL-BAZI
  4. Tez Türü: Yüksek Lisans
  5. Konular: Ulaşım, Yönetim Bilişim Sistemleri, Transportation, Management Information Systems
  6. Anahtar Kelimeler: Belirtilmemiş.
  7. Yıl: 2015
  8. Dil: İngilizce
  9. Üniversite: Coventry University
  10. Enstitü: Yurtdışı Enstitü
  11. Ana Bilim Dalı: Belirtilmemiş.
  12. Bilim Dalı: Belirtilmemiş.
  13. Sayfa Sayısı: 105

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Özet (Çeviri)

Airline industry is a very delicate industry where the profit margins are very low. Over the years of civil aviation the average profit margin is listed as less than %1. Therefore, it is essential to cut costs and increase revenue wherever is possible. To increase revenue, revenue management is used in airline industry to maximise the profit. In revenue management, the element of control system includes any operation that involves controlling the factors of offered product. One of the factors controlled is the overbooking concept. This concept is selling tickets over the offered capacity to increase capacity utilisation in case of no-show probability of ticketed passengers. There are, however, many risks involved when implementing an overbooking strategy. If the number of passengers show up for the flight exceeds the number of seats offered, the airline has to deny number of oversold tickets and they have to compensate the denied passengers, decreasing the profit. Under the unknown probability of number of passengers showing up for the flight, it is important to balance the number of overbookings that will be allowed based on several factors. It has been noted that most of the previous works used estimation or random probability on deciding the number no-show passengers which are solved through mathematical programs. This is impractical as in most cases as there is no defined/known probabilistic behaviour that could model most of the aspect of oversold tickets problems and additional limitations or preferences are neglected. The aim of this research is to solve number of overbooking problems in the airline industry for the best forecasting of the overbooking limit based on an expert system. This leads to a more satisfactory results per single-leg flight through robust decision support system on airline overbooking limit based on the expert preferences or constraints. The successful completion of this project will assist in improving the decision support system when deciding whether to overbook a particular flight or if overbook is allowed how many overbooks are optimal based on the preference of the airline.

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