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Soft Computing
Published in: Soft Computing 18/2020

27-02-2020 | Methodologies and Application

A binary differential evolution algorithm for airline revenue management: a case study

Authors: Amir Karbassi Yazdi, Mohamad Amin Kaviani, Thomas Hanne, Andres Ramos

Published in: Soft Computing | Issue 18/2020

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Abstract

In the current highly competitive airline market, many companies have failed due to their low revenue rates. For this reason, many of them have to develop strategies to increase their revenue. In this study, we develop revenue management (RM) strategy for the Iranian airline industry. More specifically, we present a mathematical model that considers some conditions not studied in previous research in order to provide a more realistic RM modeling of airlines that fits well for the special characteristics of Iranian Airways. A binary differential evolution algorithm is employed to solve the model due to the stochastic nature of data and the NP-hardness of the considered problem. To generate maximum revenue among the six types of airplanes that fly the four capital cities of Iran, the airline under investigation is advised to operate only 21 flights to those cities and cancel the rest of the flights.
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Metadata
Title
A binary differential evolution algorithm for airline revenue management: a case study
Authors
Amir Karbassi Yazdi
Mohamad Amin Kaviani
Thomas Hanne
Andres Ramos
Publication date
27-02-2020
Publisher
Springer Berlin Heidelberg
Published in
Soft Computing / Issue 18/2020
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-020-04790-2

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