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<p>The (<i>m</i>,&#xa0;<i>n</i>)-cubic quasi-rung orthopair fuzzy ((<i>m</i>,&#xa0;<i>n</i>)-CQROF) set provides a unified framework that generalizes both the interval-valued (<i>m</i>,&#xa0;<i>n</i>)-rung orthopair fuzzy set (IV(<i>m</i>,&#xa0;<i>n</i>)-ROFS) and the (<i>m</i>,&#xa0;<i>n</i>)-rung orthopair fuzzy set ((<i>m</i>,&#xa0;<i>n</i>)-ROFS). This broader model integrates the characteristics of both interval-valued and precise-valued orthopair fuzzy sets, thereby allowing decision experts to express their preferences with greater flexibility and clarity. This study introduces an aggregation approach for the (<i>m</i>,&#xa0;<i>n</i>)-CQROF set utilizing Aczel-Alsina (A-A) operations. We initiate by introducing a variety of novel A-A operations for (<i>m</i>,&#xa0;<i>n</i>)-CQROF sets and examining their mathematical characteristics. Building upon these operations, we formulate various (<i>m</i>,&#xa0;<i>n</i>)-CQROF averaging and geometric aggregation operators that effectively compile (<i>m</i>,&#xa0;<i>n</i>)-CQROF data. We also establish the distinctive features of these operators, discuss certain special cases, and delve into their fundamental results. Further, we extend the stepwise weight assessment ratio analysis (SWARA) method and integrate it with these operators to create a framework for multi-criteria group decision-making in scenarios with indeterminate weight information. Lastly, the study presents two practical case studies, complemented by an analysis of parameters and a comparative review.</p>

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Multi-criteria decision-analysis with SWARA and Aczel-Alsina aggregation for (m, n)-cubic quasi-rung orthopair fuzzy sets

  • 期刊论文

  • 发表日期：

    2025年12月24日

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  • Jawad Ali

摘要

The (m, n)-cubic quasi-rung orthopair fuzzy ((m, n)-CQROF) set provides a unified framework that generalizes both the interval-valued (m, n)-rung orthopair fuzzy set (IV(m, n)-ROFS) and the (m, n)-rung orthopair fuzzy set ((m, n)-ROFS). This broader model integrates the characteristics of both interval-valued and precise-valued orthopair fuzzy sets, thereby allowing decision experts to express their preferences with greater flexibility and clarity. This study introduces an aggregation approach for the (m, n)-CQROF set utilizing Aczel-Alsina (A-A) operations. We initiate by introducing a variety of novel A-A operations for (m, n)-CQROF sets and examining their mathematical characteristics. Building upon these operations, we formulate various (m, n)-CQROF averaging and geometric aggregation operators that effectively compile (m, n)-CQROF data. We also establish the distinctive features of these operators, discuss certain special cases, and delve into their fundamental results. Further, we extend the stepwise weight assessment ratio analysis (SWARA) method and integrate it with these operators to create a framework for multi-criteria group decision-making in scenarios with indeterminate weight information. Lastly, the study presents two practical case studies, complemented by an analysis of parameters and a comparative review.