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A GRA-based intuitionistic fuzzy multi-criteria group decision making method for personnel selection
Authors:Shi-fang Zhang  San-yang Liu
Affiliation:1. Department of Computer Science and Technology, Xidian University, Xi’an, Shaanxi 710071, China;2. Department of Mathematics, Xidian University, Xi’an, Shaanxi 710071, China;1. School of Management and Economics, University of Electronic Science and Technology of China, Chengdu 610054, China;2. Business School, Sichuan University, Chengdu, Sichuan 610065, China;1. Department of Business Administration, Universiy of Barcelona, Av. Diagonal 690, 08034 Barcelona, Spain;2. Manchester Business School, University of Manchester, M15 6PB Manchester, UK;1. School of Information, Zhejiang University of Finance & Economics, 18 Xueyuan Street, Hangzhou 310018, China;2. Research Institute of Management Science, Business School, Hohai University, Nanjing 211100, China;1. College of Information Technology, Jiangxi University of Finance and Economics, Nanchang, Jiangxi 330013, China;2. Jiangxi Key Laboratory of Data and Knowledge Engineering, Jiangxi University of Finance and Economics, Nanchang, Jiangxi 330013, China;3. College of Statistics, Jiangxi University of Finance and Economics, Nanchang, Jiangxi 330013, China
Abstract:Due to the increasing competition of globalization, selection of the most appropriate personnel is one of the key factors for an organization’s success.The importance and complexity of the personnel selection problem call for the method combining both subjective and objective assessments rather than just subjective decisions. The aim of this paper is to develop a new method for solving the decision making process. An intuitionistic fuzzy multi-criteria group decision making method with grey relational analysis (GRA) is proposed. Intuitionistic fuzzy weighted averaging (IFWA) operator is utilized to aggregate individual opinions of decision makers into a group opinion. Intuitionistic fuzzy entropy is used to obtain the entropy weights of the criteria. GRA is applied to the ranking and selection of alternatives. A numerical example for personnel selection is given to illustrate the proposed method finally.
Keywords:
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