Proper process selection during flight schedule disruption using a fuzzy multi-criteria decision-making expert system

Jangizehi, M.; Rasouli Kenari, A.; Hosseinkhani, J.

doi:10.22111/ijfs.2023.7560

Document Type : Research Paper

Authors

¹ Department of Software Engineering, University of Isfahan, Isfahan, Iran

² Faculty of Electrical and Computer Engineering, Qom University of Technology, Qom, Iran

³ Department of Computer Engineering, Zahedan Branch, Islamic Azad University, Zahedan, Iran

https://doi.org/10.22111/ijfs.2023.7560

Abstract

The aviation industry is a complicated, sensitive, and challenging phenomenon. One of the major issues in the operation of streamlined processes in this industry is the management of proper decisions during the disruption of flight schedules. Such disruptions commonly reduce customer satisfaction and the profitability of the airlines. Since there are multiple reasons for the disruption of the flight schedules along with the different possible decisions, a correct decision is very difficult to make requiring the opinions of the specialist staff. In this research, an expert model using a ``fuzzy multi-criteria decision-making" method is proposed to provide a correct decision during the disruption of the flight schedules. The results show that the most important factors that make disruption of flight schedules are arrival delays and technical failure of the airline fleet. Besides, the most important possible decisions are the announcement of the delay and canceling of the flight. Thanks to utilizing the fuzzy analytical network process, the outcomes of the proposed expert model are in good alignment with the opinions of the specialist staff. The fuzzy analytical network process determines the values of 0.5124 and 0.2621 for the magnitude of the arrival delay and technical defect respectively. This method also determines the values of 0.7042 and 0.2076 for flight delay and flight canceling as the two most important possible decisions.

Keywords

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Proper process selection during flight schedule disruption using a fuzzy multi-criteria decision-making expert system

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Volume 20, Issue 2March and April 2023Pages 121-133

Volume 20, Issue 2
March and April 2023
Pages 121-133