A dynamic multi-attribute group decision-making method with R-numbers based on MEREC and CoCoSo method

Abstract Dynamic multi-attribute group decision-making (DMAGDM) is a widespread practice in which evaluations are provided by multiple decision-makers at various times and early impact later evaluations. Additionally, attributes alternatives can be added or removed over time. An R-numbers DMAGDM method developed based on the advantages of capturing risks. This paper introduces Einstein weighted averaging (RNEWA) operator geometric (RNEWG) operator, distinct from conventional algebraic operations, examines their properties. Moreover, an expert weight determination model constructed using similarity measure R-numbers. The attribute environment also proposed with criteria removal effects (MEREC). A static rating calculation model, utilizes combination compromise solution (CoCoSo) environment, built RNEWA RNEWG operator. Furthermore, new dynamic does not require storage all decision information Finally, applicability effectiveness demonstrated through case study supply chain risk assessment manufacturing enterprises.