Fuzzy knowledge-based decisions for airline seat booking
 

Chung-Hsing Yeh and Philip Yiu-Ming Wah

School of Business Systems, Monash University, Clayton, Victoria 3800, Australia
 

Abstract

This paper presents a fuzzy knowledge-based approach to help make booking acceptance or refusal decisions in airline operations. To maximize profit, a decision has to be made about whether a booking for a lower fare seat should be accepted. The uncertainty about the actual demand, the booking cancellations and the arrival time among different passenger groups makes such a decision difficult. Very often the decision is made based on experience and knowledge of airline management, in particular when there are no sufficient historical data. To help airline management make consistent decisions, the fuzzy knowledge base developed consists of 42 linguistic decision rules in response to four commonly used input conditions in considering booking acceptance or refusal decisions. After extensive verification of the fuzzy knowledge base, a decision table is constructed to show all possible combinations among value ranges of four input conditions that lead to an acceptance decision. The rule-based form of the fuzzy knowledge base facilitates its adaptation to operation-specific settings or operator-dependent knowledge.

Keywords:  Airline seat booking, Knowledge-based, Fuzzy logic, Decision rules, Yield management, Uncertainty