An approach to multi-attribute decision making based on intuitionistic fuzzy rough Aczel-Alsina aggregation operators
Amir Hussain, Haolun Wang, Harish Garg, Kifayat Ullah
Abstract
A concept of intuitionistic fuzzy rough set based on approximations plays a vital role in coping with uncertainty. Aczel-Alsina t-norm and t-conorm are the most flexible operational laws based on the parameter for fuzzy frameworks. In multi-attribute group decision-making (MAGDM), the aim of this article is to develop some tools based on norm operations for the information fusion. In this article, intuitionistic fuzzy rough Aczel-Alsina weighted geometric operators are developed and studied their properties. Based on these operators, MAGDM algorithm is presented. The developed aggregation operators (AOs) are compared with some existing AOs, and their significance is discussed.
Topics & Concepts
Rough setNorm (philosophy)Fuzzy logicGroup decision-makingComputer scienceFuzzy setMathematicsData miningArtificial intelligenceLawPolitical scienceRough Sets and Fuzzy LogicMulti-Criteria Decision MakingFuzzy Logic and Control Systems