Multi-attribute group decision-making algorithm based on Yager norms for intuitionistic fuzzy soft numbers

Intuitionistic fuzzy soft set (IFSS) theory offers an effective and comprehensive algorithm to handle uncertainty by incorporating parameterized elements which makes it a strong technique for decision-making (DM). For the purpose to aggregate IFS numbers (IFSNs), we propose new operation rules for IFSNs. Then, by utilizing the proposed operations, we propose intuitionistic fuzzy soft Yager weighted averaging (IFSYWA) and geometric (IFSYWG) aggregation operator (AO). Further, we thoroughly examine the mathematical characteristics of the proposed IFSYWA AO and IFSYWG AO such as idempotency and monotonicity. By using the proposed IFSYWA and IFSYWG AO, we develop a multi-attribute group decision-making (MAGDM) algorithm for IFSNs environment. Usefulness of proposed MAGDM algorithm is illustrated by a real-world MAGDM problem focussed on selecting the best renewable energy project for investment.Lastly, the results confirm that the suggested AOs can be used to solve MAGDM difficulties