A dynamical hybrid method to design decision making process based on GRA approach for multiple attributes problem

This article intends to study the dynamic hybrid multi-attribute decision making (DHMADM) process, where the choice information is given in two-scale intuitionistic fuzzy numbers (IFNs) as well as interval-valued intuitionistic fuzzy numbers (IVIFNs) by the decision-makers (DMs) at distinct periods. We have contributed some new dynamic weighted aggregation operators (AOs), namely dynamic intuitionistic fuzzy Dombi weighted average (DIFDWA), weighted geometric (DIFDWG) operators, and uncertain dynamic intuitionistic fuzzy Dombi weighted average (UDIFDWA), weighted geometric (UDIFDWG) operators for interval uncertainty. Next, we have obtained the aggregated data by using these dynamic Dombi operators. Then, we apply two grey relational analysis (IF-GRA and IVIF-GRA) approach on the aggregated matrix to obtain the overall grey relational degree for each option from positive and negative ideal (PIA and NIA) alternative. Then, we evaluate each choice?s relative relational degree from the positive to get the final rank. Finally, we demonstrate the proposed model with a numerical example to compare the proposed model for applicability and validity.

Automated summary

This article studies the dynamic hybrid multi-attribute decision making process, proposes new dynamic weighted aggregation operators, and applies grey relational analysis to analyze aggregated data for final ranking.