P-J Matching Model of Knowledge Workers | Zendy

Lili Zhang | Zendy; Fei Wei | Zendy; Li Wang | Zendy

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P-J Matching Model of Knowledge Workers

Author(s) -

Lili Zhang,

Fei Wei,

Li Wang

Publication year - 2015

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2015.08.163

Subject(s) - computer science , construct (python library) , matching (statistics) , extension (predicate logic) , fuzzy logic , position (finance) , hierarchy , fuzzy number , membership function , data mining , artificial intelligence , function (biology) , fuzzy set , mathematics , statistics , market economy , finance , evolutionary biology , economics , biology , programming language

This article develops a decision analysis method that optimizes the knowledge worker-position match considering various characteristics of knowledge workers. First, we construct hierarchy evaluation index systems that match the knowledge worker with the right position. Second, we transform the multiple indicator linguistic assessment information of knowledge workers and positions into the form of triangular fuzzy numbers, compute and analyze the fuzzy numbers based on the extension principle of fuzzy numbers, and then construct multi-objective optimization model containing fuzzy numbers. Third, we use the membership function method of fuzzy number in order to transform and solve the model. Lastly, samples are collected in an iron and steel organization. Results indicate the feasibility and effectiveness of the method

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