Open AccessMultiple Attribute Group Decision Making Methods Using Numerical Methods of Intuitionistic Triangular Fuzzy Sets
Author(s) -
S. Akila,
Philip J. Robinson
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1377/1/012022
Subject(s) - mathematics , group decision making , ranking (information retrieval) , operator (biology) , mathematical optimization , fuzzy number , score , group (periodic table) , fuzzy logic , algorithm , computer science , fuzzy set , artificial intelligence , statistics , biochemistry , chemistry , organic chemistry , repressor , political science , transcription factor , law , gene
Solving Multiple Attribute Group Decision Making (MAGDM) problems has become one of the most important research in the recent trends. The information or data is in the form of Intuitionistic Triangular Fuzzy Number (ITrFN). The weights are derived from the numerical solutions of partial differential equations of Laplace’s equation and poisson`s equation. The weights obtained from the methods are applied in decision making problems. The Intuitionistic Triangular Fuzzy Ordered Weighted Averaging (ITrFOWA) operator and the Intuitionistic Triangular Fuzzy Hybrid Aggregation (ITrFHA) operator are used to combine the decision matrix. Distance function is used as a tool for ranking the best alternatives. Numerical illustration is proposed to show the effectiveness of the method.