Multi-criteria evaluation of alternative-fuel vehicles via a hierarchical hesitant fuzzy linguistic model
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The hesitant fuzzy AHP allows the superiority relationship between criteria to be determined more flexibly than traditional AHP.
“For instance, while the traditional AHP requires selecting one of the exact numbers from the 1-9 scale to express the superiority relationship between criteria x and y, the hesitant fuzzy AHP allows this relationship to be determined more flexibly [22], [50].”
From Trustworthiness Evaluation of Large Language Models Using Multi-Criteria Decision Making (2025) · cites this paper as [22]
The hesitant fuzzy AHP technique has proven to be as valid as the traditional AHP technique.
“This technique, which belongs to the group of methods extended with fuzzy numbers, has been frequently used in the literature and has proven to be as valid as the traditional AHP technique [17], [22], [23], [24], [48].”
From Trustworthiness Evaluation of Large Language Models Using Multi-Criteria Decision Making (2025) · cites this paper as [22]
Hesitant fuzzy numbers provide an effective solution in cases where experts are unable to determine the superiority of one option over another.
“A key distinguishing feature of hesitant fuzzy numbers compared to other scales based on fuzzy numbers is that they provide an effective solution in cases where experts are unable to determine the superiority of one option over another [22], [49].”
From Trustworthiness Evaluation of Large Language Models Using Multi-Criteria Decision Making (2025) · cites this paper as [22]
The hesitant fuzzy AHP approach offers greater flexibility by accommodating expert hesitation in comparative evaluations and utilizing linguistic expressions instead of rigid numerical scales.
“This approach offers greater flexibility by accommodating expert hesitation in comparative evaluations and utilizing linguistic expressions instead of rigid numerical scales [17], [22], [23], [24].”
From Trustworthiness Evaluation of Large Language Models Using Multi-Criteria Decision Making (2025) · cites this paper as [22]
Cited by
Sorted by citations
Alemi-Ardakani, M., Milani, A. S., Yannacopoulos, S., & Shokouhi, G. (2016) · Expert Systems with Applications · doi:10.1016/j.eswa.2015.11.003 · Cited by 230 · see citing works
Alternative Fuel Selection Framework toward Decarbonizing Maritime Deep-Sea Shipping
Moshiul, A. M., Mohammad, R., & Hira, F. A. (2023) · Sustainability · doi:10.3390/su15065571 · Cited by 55 · see citing works
Trustworthiness Evaluation of Large Language Models Using Multi-Criteria Decision Making
Aksoy, M., Adem, A., & Dağdeviren, M. (2025) · IEEE Access · doi:10.1109/access.2025.3612568 · Cited by 10 · see citing works
“This approach offers greater flexibility by accommodating expert hesitation in comparative evaluations and utilizing linguistic expressions instead of rigid numerical scales [17], [22], [23], [24].”
Influential
- Authors
- Yavuz, M., Oztaysi, B., Cevik Onar, S., & Kahraman, C.
- Affiliations
- University of Alabama (US)
- Istanbul Technical University (TR)
- Corresponding author
- Yavuz, Mesut
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2015-04
- Volume
- 42
- Issue
- 5
- Pages
- 2835-2848
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W2020679445
- Cited by
- 179
- References
- 0
- Citations by year
- 2026: 4 · 2025: 12 · 2024: 7 · 2023: 17 · 2022: 13 · 2021: 15 · 2020: 18 · 2019: 25 · 2018: 24 · 2017: 17 · 2016: 18 · 2015: 9
- FWCI
- 18.53
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Expert Systems with Applications (publishedVersion)
- Istanbul Technical University Academic Open Archive (Istanbul Technical University) (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Multi-Criteria Decision Making
- Physical Sciences › Environmental Science › Ecological Modeling › Evaluation Methods in Various Fields
- Social Sciences › Decision Sciences › Management Science and Operations Research › Fuzzy and Soft Set Theory
- Keywords
- alternative fuel vehicles, vehicle selection, multi-criteria decision making, hierarchical decision model, electric vehicles, sensitivity analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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