Interval valued fuzzy sets based on normal forms
Fuzzy Sets and Systems
A method for inference in approximate reasoning based on interval-valued fuzzy sets
Fuzzy Sets and Systems
Extensions of the TOPSIS for group decision-making under fuzzy environment
Fuzzy Sets and Systems
Some algebraic properties and a distance measure for interval-valued fuzzy numbers
Information Sciences—Applications: An International Journal
Arithmetic operators in interval-valued fuzzy set theory
Information Sciences: an International Journal
Uncertainty measures for interval type-2 fuzzy sets
Information Sciences: an International Journal
Information Sciences: an International Journal
Fuzzy rough set theory for the interval-valued fuzzy information systems
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Interval-valued fuzzy sets constructed from matrices: Application to edge detection
Fuzzy Sets and Systems
Combination of interval-valued fuzzy set and soft set
Computers & Mathematics with Applications
Fuzzy filter based on interval-valued fuzzy sets for image filtering
Fuzzy Sets and Systems
Environmental Modelling & Software
Advances and challenges in interval-valued fuzzy logic
Fuzzy Sets and Systems
Extension of the ELECTRE method based on interval-valued fuzzy sets
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special issue on Digital Information Forensics
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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Multiple Attributes Decision Making MADM is the process of finding the best candidate and involves the evaluation and selection among a finite number of potential candidates to solve real-life complex decision problems. In classical MADM methods, the relative importance of the conflicting criteria and performance ratings of candidates are determined precisely. However, in real-world systems related to human resource management, decision making problems are often uncertain or vague, and because of the lack of information, the future state of these systems cannot be known completely. Moreover, if decision makers cannot reach an agreement on the method of defining linguistic variables based on the traditional fuzzy sets, the Interval-Valued Fuzzy Sets IVFSs theory can provide a more accurate and practical modeling. This paper presents an Interval-Valued Fuzzy Preference Selection Index IVF-PSI method aiming at solving complex decision making problems, in which the performance ratings of candidates are described by using the concept of the IVFSs. Finally, the executive procedure of the proposed IVF-PSI method is illustrated by applying it to the expatriate selection process from the viewpoint of human resource managers.