Abstract
In this paper a revised Intuitionistic Fuzzy Max-Min Average Composition Method is proposed to construct the decision method for the selection of the professional students based on their skills by the recruiters using the operations of Intuitionistic Fuzzy Soft Matrices. In Shanmugasundaram et al. (2014), Intuitionistic Fuzzy Max-Min Average Composition Method was introduced and applied in Medical diagnosis problem. Sanchez’s approach (Sanchez (1979)) for decision making is studied and the concept is modified for the application of Intuitionistic fuzzy soft set theory. Through a survey, the opportunities and selection of the students with the help of Intuitionistic fuzzy soft matrix operations along with Intuitionistic fuzzy max-min average composition method is discussed.
Highlights
Soft set theory was initiated by the Russian researcher Molodtsov [1]; he proposed soft set as a completely generic mathematical tool for modeling uncertainties
An attempt has been made to provide a formal model of the process to study the selection of professional students by using intuitionistic fuzzy soft matrix (IFSM) theory and implement it in the form of field recommendation system
The basic definitions of intuitionistic fuzzy soft set theory that are useful for subsequent discussions are given
Summary
Soft set theory was initiated by the Russian researcher Molodtsov [1]; he proposed soft set as a completely generic mathematical tool for modeling uncertainties. Maji et al [2, 3] applied this theory to several directions for dealing with the problems in uncertainty and imprecision. An attempt has been made to provide a formal model of the process to study the selection of professional students by using IFSM theory and implement it in the form of field recommendation system. This is the system by which the recruiters use their knowledge to infer the selection from the skills displayed by the test results of the students and based on their selection criteria. Advances in Fuzzy Systems better results than the existing max-min composition method [15, 16]
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