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. 2025 Apr 12;15(1):12637.
doi: 10.1038/s41598-025-95981-0.

An integrated multi criteria decision making method using dual hesitant fuzzy sets with application for unmanned aerial vehicle selection

Fei Gao  1
Affiliations

An integrated multi criteria decision making method using dual hesitant fuzzy sets with application for unmanned aerial vehicle selection

Fei Gao. Sci Rep. .

Abstract

Unmanned aerial vehicles (UAVs) have gained widespread attention in recent years due to their expanding applications across various industrial sectors. Selecting the most suitable UAV for a given task is a critical decision-making challenge, which is typically modeled as a multi-criteria decision-making (MCDM) problem. However, expert assessments in such selection processes often involve considerable uncertainty and hesitation. To address this, this paper proposes a novel integrated MCDM framework that combines dual hesitant fuzzy sets (DHFSs), the best-worst method (BWM), and the MULTIMOORA method to evaluate and rank UAV alternatives. In the proposed method, DHFSs are employed to capture both membership and non-membership degrees of expert assessments under uncertainty, while expert weights are objectively determined based on the entropy of their assessments. Criteria weights are then calculated using an extended dual hesitant fuzzy BWM. Subsequently, the MULTIMOORA method is extended into the dual hesitant fuzzy environment, where UAV alternatives are evaluated from three perspectives: the ratio system, the extended reference point approach, and the full multiplicative form, and the evaluation results are aggregated to generate a comprehensive and reliable final ranking. To demonstrate the practicality and effectiveness of the proposed method, a case study on UAV selection for power line inspection is presented. The results show that the proposed approach effectively handles uncertainty, produces stable and consistent rankings, and offers reliable decision support under uncertain and fuzzy conditions. The proposed method provides a flexible and systematic decision-making tool that can assist decision-makers in solving UAV selection problems in complex, real-world scenarios.

Keywords: Dual hesitant fuzzy sets; MULTIMOORA; Multi criteria decision making; Unmanned aerial vehicle.

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Conflict of interest statement

Declarations. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Framework of the proposed method.
Algorithm 1
Algorithm 1
The proposed DHFS-based UAV selection method.
Fig. 2
Fig. 2
Changes in the evaluation results with changes in criterion weight of formula image.
Fig. 3
Fig. 3
Changes in the evaluation results with changes in criterion weight of formula image.
Fig. 4
Fig. 4
Changes in the evaluation results with changes in criterion weight of formula image.
Fig. 5
Fig. 5
Changes in the evaluation results with changes in criterion weight of formula image.
Fig. 6
Fig. 6
Changes in the evaluation results with changes in criterion weight of formula image.
Fig. 7
Fig. 7
Changes in the evaluation results with changes in criterion weight of formula image.
Fig. 8
Fig. 8
Comparison of results of different values of formula image.
Fig. 9
Fig. 9
Spearman’s rank correlation coefficients of the comparative methods.
See this image and copyright information in PMC

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