Dynamic Chaotic Multi-Attribute Group Decision Making under Weighted T-Spherical Fuzzy Soft Rough Sets

In this article, the parameter of decision maker’s familiarity with attributes alternatives is introduced for first time in dynamic multi-attribute group making to avoid disadvantages arising from inappropriate grouping makers. We combine it fuzzy soft rough set theory and multi-attribute-grouping obtain a new model, i.e., chaotic multiple-attribute making. Second, we provide an algorithm solving model under weighted T-spherical set, which can not only achieve symmetry between evaluation information but also establish good symmetrical balance makers (evaluation indexes). Finally, specific numerical computation case proposed illustrate convenience effectiveness our constructed algorithm. Our contributions literature are: (1) This makes given decision-making (DCMAGDM) more general closer actual situation; (2) combined make realistic reflect situation. addition, choice allows maker engage sensible rather than sticking size choices; (3) convenient sorting/ranking based on sets.