Circular Intuitionistic Fuzzy AHP: An Application in Manufacturing Sector

Alimohammadlou, Moslem; Alinejad, Saeed; Khoshsepehr, Zahra; Safari, Mohsen; Jafari, Yalda; Tajodin, Asefeh; Mohammadi, Sahar Sadat

doi:10.1007/978-3-031-39438-6_17

Studies in Fuzziness and Soft Computing

2023

DOI: 10.1007/978-3-031-39438-6_17

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Circular Intuitionistic Fuzzy AHP: An Application in Manufacturing Sector

Moslem Alimohammadlou,

Saeed Alinejad,

Zahra Khoshsepehr

et al.

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2024

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Cited by 3 publications

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Parametric circular intuitionistic fuzzy information measures and multi-criteria decision making with extended TOPSIS

Bozyiğit,

Ünver

2024

Granul. Comput.

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Parametric circular intuitionistic fuzzy information measures and multi-criteria decision making with extended TOPSIS

Bozyiğit,

Ünver

2024

Granul. Comput.

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AI-Driven LOPCOW-AROMAN Framework and Topological Data Analysis Using Circular Intuitionistic Fuzzy Information: Healthcare Supply Chain Innovation

Riaz,

Qamar,

Tariq

et al. 2024

Mathematics

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Artificial intelligence (AI) stands out as a significant technological innovation, driving progress in diverse areas such as big data analysis, supply chain management, energy efficiency, sustainable development, etc. The present study investigates how AI could contribute to the sustainability of the healthcare supply chain (HSC) and managing medical needs. Medical organizations can boost the logistics of their tasks, reduce pharmaceutical trash, and strengthen revenue projections through the adoption of AI tools. This study aims to provide a structured evaluation of AI-driven solutions for enhancing healthcare supply chain robustness, especially under conditions of uncertainty and complex logistics demands. To determine the investment value of AI applications in HSC management, the current research adopted a revolutionary multi-criteria decision-making (MCDM) methodology tailored to the healthcare sector’s unique demands, including six critical factors. In light of these criteria, six highly technologically advanced AI-based solutions are examined. The implementation of a circular intuitionistic fuzzy set (CIFS) in the instance discussed provides a versatile and expressive way to describe vague and uncertain information. This study leverages the CIF topology to address data complexities and uncover the underlying structural features of a large dataset. At the outset, we adopted the LOPCOW approach, which includes logarithmic variation to assign weights to criteria, whereas the AROMAN method utilizes a powerful two-step normalization technique to rank alternatives, hence guaranteeing a trustworthy and accurate appraisal. A substantial degree of robustness was confirmed by the technique following a comparison of the operators as well as sensitivity testing.

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Extension operators of circular intuitionistic fuzzy sets with triangular norms and conorms: Exploring a domain radius

Pratama,

Yusoff,

Abdullah

et al. 2024

MATH

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<abstract><p>The circular intuitionistic fuzzy set (<italic>CIFS</italic>) extends the concept of <italic>IFS</italic>, representing each set element with a circular area on the <italic>IFS</italic> interpretation triangle (<italic>IFIT</italic>). Each element in <italic>CIFS</italic> is characterized not only by membership and non-membership degrees but also by a radius, indicating the imprecise areas of these degrees. While some basic operations have been defined for <italic>CIFS</italic>, not all have been thoroughly explored and generalized. The radius domain has been extended from $ [0, 1] $ to $ [0, \sqrt{2}] $. However, the operations on the radius domain are limited to $ min $ and $ max $. We aimed to address these limitations and further explore the theory of <italic>CIFS</italic>, focusing on operations for membership and non-membership degrees as well as radius domains. First, we proposed new radius operations on <italic>CIFS</italic> with a domain $ [0, \psi] $, where $ \psi \in [1, \sqrt{2}] $, called a radius algebraic product (<italic>RAP</italic>) and radius algebraic sum (<italic>RAS</italic>). Second, we developed basic operators for generalized union and intersection operations on <italic>CIFS</italic> based on triangular norms and conorms, investigating their algebraic properties. Finally, we explored negation and modal operators based on proposed radius conditions and examined their characteristics. This research contributes to a more explicit understanding of the properties and capabilities of <italic>CIFS</italic>, providing valuable insights into its potential applications, particularly in decision-making theory.</p></abstract>

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Circular Intuitionistic Fuzzy AHP: An Application in Manufacturing Sector

Cited by 3 publications

References 64 publications

Parametric circular intuitionistic fuzzy information measures and multi-criteria decision making with extended TOPSIS

Parametric circular intuitionistic fuzzy information measures and multi-criteria decision making with extended TOPSIS

AI-Driven LOPCOW-AROMAN Framework and Topological Data Analysis Using Circular Intuitionistic Fuzzy Information: Healthcare Supply Chain Innovation

Extension operators of circular intuitionistic fuzzy sets with triangular norms and conorms: Exploring a domain radius

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