The Relationship Between Airline Ticket Pricing Model and Demand Uncertainty (Case Study: Iran Airtour Airline)

Abstract

The present study considered a problem in optimizing the price of airline tickets regarding the demand uncertainty, ticket cancellation rate, absence rate, and airline ticket classification. In addition, the relevant mathematical model was developed by considering the multiplicative uncertainty model. Genetic algorithm and LINGO were used to solve the model since the model was a mixed integer non-linear mathematical programming and its objective function was non-concave. The optimal ticket prices were obtained by considering the limitations raised in the model. Eventually, comparing the results of the genetic algorithm to Lingo showed that the genetic algorithm results were more satisfactory. The observations and results on a sample of 30 random problems revealed that the genetic algorithm developed in this study is appropriate for solving the model with actual data in the real world.