GRA method for multiple attribute decision making with incomplete weight information in intuitionistic fuzzy setting |
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| Authors: | Gui-Wu Wei |
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| Affiliation: | 1. Business School, Sichuan University, Chengdu 610064, China;2. Andalusian Research Institute on Data Science and Computational Intelligence (DaSCI), University of Granada, Granada 18071, Spain;3. Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia;1. Business School, Sichuan University, Chengdu, 610065, China;2. Centre for Computational Intelligence, Faculty of Technology, De Montfort University, Leicester, UK;3. Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain;4. Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah, Saudi Arabia;1. Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan;2. Department of Information Management, Chienkuo Technology University, Changhua, Taiwan;3. Department of Kinesiology Health Leisure Studies, Chienkuo Technology University, Changhua, Taiwan |
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| Abstract: | The aim of this paper is to investigate the multiple attribute decision-making problems with intuitionistic fuzzy information, in which the information about attribute weights is incompletely known, and the attribute values take the form of intuitionistic fuzzy numbers. In order to get the weight vector of the attribute, we establish an optimization model based on the basic ideal of traditional grey relational analysis (GRA) method, by which the attribute weights can be determined. Then, based on the traditional GRA method, calculation steps for solving intuitionistic fuzzy multiple attribute decision-making problems with incompletely known weight information are given. The degree of grey relation between every alternative and positive-ideal solution and negative-ideal solution are calculated. Then, a relative relational degree is defined to determine the ranking order of all alternatives by calculating the degree of grey relation to both the positive-ideal solution (PIS) and negative-ideal solution (NIS) simultaneously. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness. |
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