A Novel Multi-Criteria Group Decision-Making Approach Based on Bonferroni and Heronian Mean Operators under Hesitant 2-Tuple Linguistic Environment

Ambiguous and uncertain facts can be handled using a hesitant 2-tuple linguistic set (H2TLS), an important expansion of the set. The vagueness uncertainty data grabbed by aggregation operators. Therefore, operators play role in computational processes to merge information provided decision makers (DMs). Furthermore, operator is potential mechanism for merging multisource which synonymous with cooperative preference. need studied analyzed from various perspectives represent complex choice situations more readily capture diverse experiences DMs. In this manuscript, we propose some valuable operational laws H2TLS. These new work through individual words collection translation parameters. We introduced weighted average (H2TLWA) solve multi-criteria group decision-making (MCGDM) problems. also define Bonferroni mean (H2TLBM) operator, geometric (H2TLGBM) Heronian (H2TLHM) (H2TLGHM) based on novel proposed paper. addition, subtraction, multiplication, division, scalar power complement their respective properties. An application example comparison analysis were examined show usefulness practicality work.