Circular Intuitionistic Fuzzy Dombi Aggregation Operators and their Application to Marine Fuel Selection | Zendy

Nuraini Rahim | Zendy; Binyamin Yusoff | Zendy; Lazim Abdullah | Zendy; Dian Pratama | Zendy

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Circular Intuitionistic Fuzzy Dombi Aggregation Operators and their Application to Marine Fuel Selection

Author(s) -

Nuraini Rahim,

Binyamin Yusoff,

Lazim Abdullah,

Dian Pratama

Publication year - 2025

Publication title -

ieee access

Language(s) - English

Resource type - Magazines

SCImago Journal Rank - 0.587

H-Index - 127

eISSN - 2169-3536

DOI - 10.1109/access.2025.3590550

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

Higher-order fuzzy sets have emerged as effective tools for decision-making under uncertainty. Among these, the circular intuitionistic fuzzy set (CIFS) has recently been introduced to better represent uncertain information. In a CIFS, each element is modelled as a circular area defined by a radius, with membership and non-membership degrees located at its center. Aggregation operators play a crucial role in synthesizing multiple inputs into representative ones. Among the well-known operators, Dombi operators, comprising the Dombi t-norm and t-conorm, offer significant flexibility due to their adjustable parameters. However, existing CIFS-based aggregation operators are typically defined for r ∈ [0, 1], which only partially covers the intuitionistic fuzzy interpretation triangle. This study extends Dombi aggregation operators to the full CIFS domain, r ∈ [0, √ 2] and examines their mathematical properties in accordance with fundamental algebraic laws. Specifically, we introduce the CIF Dombi Weighted Averaging, CIF Dombi Ordered Weighted Averaging, CIF Dombi Weighted Geometric, and CIF Dombi Ordered Weighted Geometric operators. In addition, existing score functions for ranking CIFS values do not adequately account for the influence of the radius, which should prioritize smaller r values due to their lower uncertainty. Therefore, we propose an alternative score function to improve the consistency and accuracy of CIFS value ranking. Based on these developments, a multi-criteria decision-making (MCDM) model is constructed within the CIFS environment. The model is applied to a real-world problem of marine fuel selection, demonstrating its practicality and robustness. Comparative and sensitivity analyses further validate the model’s performance. The findings highlight the effectiveness of the proposed operators in enhancing decision-making under uncertainty, offering valuable insights for policymakers and stakeholders in the marine fuel sector.

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