Interval type-2 hesitant fuzzy Entropy-based WASPAS approach for aircraft type selection

Deveci, Muhammet; Öner, Sultan Ceren; Ciftci, Muharrem Enis; Özcan, Ender; Pamucar, Dragan

Abstract

Choosing the most appropriate aircraft type for a given route is one of the crucial issues that the decision makers at airline companies have to address under uncertainty based on various commercial, marketing and operational criteria. A novel multi-criteria decision making approach integrating Entropy-based Weighted Aggregated Sum Product Assessment (WASPAS) method and interval type-2 hesitant fuzzy sets (IT2HFS) is introduced for tackling this problem and tested using a particular case study obtained from a full service carrier in Turkey. This study contributes to representing and handling degrees of uncertainty in the decision making process of aircraft type selection based on the IT2HFS. The results showed that Airbus 32C is the suitable alternative for a given route in between Kuwait and Istanbul airports. The experts evaluated the results and confirmed that the proposed approach is the most suitable one when compared to four other IT2HFS based approaches.

Citation

Deveci, M., Öner, S. C., Ciftci, M. E., Özcan, E., & Pamucar, D. (2022). Interval type-2 hesitant fuzzy Entropy-based WASPAS approach for aircraft type selection. Applied Soft Computing, 114, Article 108076. https://doi.org/10.1016/j.asoc.2021.108076

• Journal Article Type: Article
• Acceptance Date: Nov 8, 2021
• Online Publication Date: Nov 23, 2021
• Publication Date: 2022-01
• Deposit Date: Dec 2, 2021
• Publicly Available Date: Nov 24, 2022
• Journal: Applied Soft Computing
• Print ISSN: 1568-4946
• Electronic ISSN: 1872-9681
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 114
• Article Number: 108076
• DOI: https://doi.org/10.1016/j.asoc.2021.108076
• Keywords: Software
• Public URL: https://nottingham-repository.worktribe.com/output/6847111
• Publisher URL: https://www.sciencedirect.com/science/article/abs/pii/S1568494621009790?via%3Dihub