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<p>This article purposes to put forward a novel multi-criteria group decision making (MCGDM) methodology based on the propound partitioned Maclaurin symmetric mean (PMSMS) operators. For this, first probabilistic hesitant fuzzy (PHF) PMSM operator, its weighted form, i.e., PHF weighted partitioned Maclaurin symmetric mean (PHFWPMSM) operator, is devised to tackle the situations where the criteria are cut into different classes, and there are interrelationships among multiple criteria in same class whilst the criteria in different classes are unrelated. Meanwhile, we study some required properties and peculiar cases of these operators. Based on these novel operators, we develop an MCGDM methodology for PHF setting. At last, a case study is provided to elaborate the practicality of the suggested approach, followed by comparative analysis with predominating studies.</p>

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Probabilistic hesitant fuzzy group decision analysis using partitioned Maclaurin symmetric mean operators

  • 期刊论文

  • 发表日期：

    2025年5月16日

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  • Jawad Ali

摘要

This article purposes to put forward a novel multi-criteria group decision making (MCGDM) methodology based on the propound partitioned Maclaurin symmetric mean (PMSMS) operators. For this, first probabilistic hesitant fuzzy (PHF) PMSM operator, its weighted form, i.e., PHF weighted partitioned Maclaurin symmetric mean (PHFWPMSM) operator, is devised to tackle the situations where the criteria are cut into different classes, and there are interrelationships among multiple criteria in same class whilst the criteria in different classes are unrelated. Meanwhile, we study some required properties and peculiar cases of these operators. Based on these novel operators, we develop an MCGDM methodology for PHF setting. At last, a case study is provided to elaborate the practicality of the suggested approach, followed by comparative analysis with predominating studies.