A new method of <scp>multi‐attribute group decision making</scp> based on hesitant fuzzy soft expert information

Interesting insights into uncertain multi-attribute decision-making systems have come from the theory of hesitant fuzzy sets. Outputs become more reliable when a decision-maker is not forced to produce one single assessment in presence hesitation. Hesitancy environments grants flexibility decision-maker, therefore enhancing validity all subsequent results. Due these facts, hesitation has landmark enhancement fuzzy-soft-inspired theories, and techniques using models such as soft sets or (fuzzy) N $$ -soft thrived. However, literature lacks comparable improvement for expert information. The main goal this paper integration both fuzziness with characteristics resulting hybrid model called set, its utilization multiple attribute group (MAGDM) will be investigated too. To that purpose, we first study required algebraic operations properties (subsethood equality, complement, union, intersection, plus AND OR operation). Respective numerical examples illustrate their utilization. We also establish some important laws sets, including commutativity, associativity, distributivity, De Morgan's laws. Moreover, define four novel types level three which are: t -level regarding threshold, mid-level top-level Armed tools, present natural algorithm MAGDM under information accompanied by an illustrative application concerns selection problem samples electric vehicles manufactured different companies. This followed comparison existing mathematical tools order show advantages our work over them. In end, provide future research directions.