Open AccessFP-intuitionistic multi fuzzy N-soft set and its induced FP-Hesitant N soft set in decision-making
Author(s) -
Ajoy Kanti Das,
Carlos Granados
Publication year - 2022
Publication title -
decision making. applications in management and engineering/decision making: applications in management and engineering
Language(s) - English
Resource type - Journals
eISSN - 2620-0104
pISSN - 2560-6018
DOI - 10.31181/dmame181221045d
Subject(s) - soft set , parameterized complexity , vagueness , group decision making , ranking (information retrieval) , fuzzy set , computer science , set (abstract data type) , fuzzy logic , mathematics , fuzzy set operations , artificial intelligence , data mining , algorithm , political science , law , programming language
Intuitionistic fuzzy sets (IFSs) can effectively represent and simulate the uncertainty and diversity of judgment information offered by decision-makers (DMs). In comparison to fuzzy sets (FSs), IFSs are highly beneficial for expressing vagueness and uncertainty more accurately. As a result, in this research work, we offer an approach for solving group decision-making problems (GDMPs) with fuzzy parameterized intuitionistic multi fuzzy N-soft set (briefly, FPIMFNSS) of dimension q by introducing its induced fuzzy parameterized hesitant N-soft set (FPHNSS) as an extension of the multi-fuzzy N-soft set (MFNSS) based group decision-making method (GDMM). In this study, we use the proposed GDMM to solve a real-life GDMP involving candidate eligibility for a single vacant position advertised by an IT firm and compare the ranking performances of the proposed GDMM with the Fatimah-Alcantud method.