Linguistic Extension for Group Multicriteria Project Manager Selection | Zendy

Javad Dodangeh | Zendy; Shahryar Sorooshian | Zendy; Ali Reza Afshari | Zendy

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Linguistic Extension for Group Multicriteria Project Manager Selection

Author(s) -

Javad Dodangeh,

Shahryar Sorooshian,

Ali Reza Afshari

Publication year - 2014

Publication title -

journal of applied mathematics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.307

H-Index - 43

eISSN - 1687-0042

pISSN - 1110-757X

DOI - 10.1155/2014/570398

Subject(s) - vagueness , multiple criteria decision analysis , selection (genetic algorithm) , computer science , task (project management) , management science , process (computing) , extension (predicate logic) , fuzzy logic , resource (disambiguation) , group decision making , human resource management , knowledge management , process management , artificial intelligence , operations research , mathematics , business , engineering , systems engineering , psychology , computer network , social psychology , programming language , operating system

Qualified human resource selection is one of the organizational key success factors. Since choosing the best candidate to fill the defined vacancy in a company is a complex task, intelligence analytical methods would be required to deal with this important issue. Regarding the vagueness and uncertainty of human resource selection process, it requires the linguistic extension of multicriteria decision making (MCDM) models for robust recruitment. This research is aimed to develop a fuzzy MCDM model for linguistic reasoning under new fuzzy group decision making. The new linguistic reasoning for group decision making is able to aggregate subjective evaluation of the decision makers and hence create an opportunity to perform more robust human resource selection procedures. A numerical example demonstrates possibilities for the improvement of human resource management and any other business decision areas through applying the proposed model

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