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<p>As an extension of intuitionistic fuzzy sets, Atanassov introduced the circular intuitionistic fuzzy set (CIFS) in 2020. On extending the work on CIFS, this study develops a new similarity measure for CIFS. The objective of this study is to develop a multi-criteria decision-making (MCDM) method by integrating a novel similarity measure and the Archimedean t-norm and t-conorm (ATU)-based WASPAS method for CISF. The developed similarity measure for CIFS is applied to determine the weight of criteria, while the ATU-based WASPAS method is used to rank the alternatives. To illustrate the applicability of this method, a problem of municipal solid waste management scenario evaluation is discussed. Sensitivity and comparative analysis are performed to demonstrate the method’s robustness, flexibility, and the validity of the final results. The findings indicate that the proposed MCDM approach offers greater flexibility and yields more realistic outcomes within the CIFS environment.</p>

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Novel similarity measure and Archimedean t-norm and t-conorm-based WASPAS method for circular intuitionistic fuzzy sets to evaluate municipal solid waste management scenarios

  • 期刊论文

  • 发表日期：

    2026年2月7日

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  • Vinay Pandey,
  • Komal

摘要

As an extension of intuitionistic fuzzy sets, Atanassov introduced the circular intuitionistic fuzzy set (CIFS) in 2020. On extending the work on CIFS, this study develops a new similarity measure for CIFS. The objective of this study is to develop a multi-criteria decision-making (MCDM) method by integrating a novel similarity measure and the Archimedean t-norm and t-conorm (ATU)-based WASPAS method for CISF. The developed similarity measure for CIFS is applied to determine the weight of criteria, while the ATU-based WASPAS method is used to rank the alternatives. To illustrate the applicability of this method, a problem of municipal solid waste management scenario evaluation is discussed. Sensitivity and comparative analysis are performed to demonstrate the method’s robustness, flexibility, and the validity of the final results. The findings indicate that the proposed MCDM approach offers greater flexibility and yields more realistic outcomes within the CIFS environment.