Evidence map›Paper›PMID 41912690›Full record

ArticleScientific reports2026

An integrated VIKOR-AHP method for green energy systems based on q-fractional hesitant fuzzy multi-criteria decision-making.

Hariwan Fadhil M Salih, Zanyar A Ameen, Badr Alharbi, Baravan A Asaad

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Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Hariwan Fadhil M SalihDepartment of Mathematics, College of Science, University of Duhok, 42001, Duhok, Iraq.
Zanyar A AmeenDepartment of Mathematics, College of Science, University of Duhok, 42001, Duhok, Iraq. zanyar.ameen@uod.ac.
Badr AlharbiDepartment of Mathematics, Al Jumum University College, Umm Al-Qura University, 24381, Makkah, Saudi Arabia.
Baravan A AsaadDepartment of Mathematics, College of Science, University of Zakho, Zakho 42002, Zakho, Iraq.

Funding

Umm Al-Qura University 26UQU4281756GSSR02
6 · The paper itself

Abstract

The q-fractional hesitant fuzzy sets (q-FHFSs) extend the conventional hesitant and intuitionistic fuzzy sets by providing a richer framework for representing uncertainty. This paper proposes an integrated VIKOR-AHP framework based on q-FHFSs to enhance multi-criteria decision-making (MCDM) under uncertain conditions. To address the challenge of comparing fractional and heterogeneous hesitant elements, this study develops an LCM-based generalized distance measure for q-fractional hesitant fuzzy numbers, enabling consistent comparison among hesitant elements with different cardinalities. As criteria weights are inherently subjective, the AHP method is used to systematically derive objective priority weights. The proposed VIKOR-AHP hybrid model improves flexibility in handling fractional hesitancy and conflicting criteria, while preserving mathematical rigor in distance quantification. To demonstrate its applicability, the model is applied to the selection of Green Energy Systems, evaluated under selected subcriteria from Cavallaro and Ciraolo's list of sustainability criteria. A sensitivity analysis is conducted to examine the influence of parameter q. Finally, a comparative evaluation against q-fractional hesitant fuzzy TOPSIS (q-FHF TOPSIS), hesitant q-rung orthopair fuzzy TOPSIS (Hq-ROF TOPSIS), hesitant q-rung orthopair fuzzy VIKOR (Hq-ROF VIKOR) and hesitant fuzzy VIKOR (HF VIKOR) across varying q values confirms the effectiveness and robustness of the proposed decision-making method.

Indexed as

Decision-makingGeneralized distance measureLCMq-fractional hesitant fuzzy setTOPSISVIKOR

Identifiers

PMID41912690
PMCPMC13039350

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