A Projection Method for Multiple Attribute Group Decision Making with Intuitionistic Fuzzy Information

2013-10-11
A Projection Method for Multiple Attribute Group Decision Making with Intuitionistic Fuzzy Information

Abstract. The aim of this paper is to investigate intuitionistic fuzzy multiple attribute group decision making problems where the attribute values provided by experts are expressed in intuitionistic fuzzy numbers, and the weight information about the experts is to be determined. We present a new method to derive the weights of experts and rank the preference order of alternatives based on projection models.We first derive the weights of the decision makers according to the projection of the individual decision on the ideal decision. The expert has a largeweight if his evaluation value is close to the ideal decision, and has a small weight if his evaluation value is far from the ideal decision. Then, based on the weighted projection of the alternatives on the intuitionistic fuzzy ideal solution (IFIS), we develop a straightforward and practical algorithm to rank alternatives. Furthermore, we extend the developed model and algorithm to the multiple attribute group decision making problems with interval-valued intuitionistic fuzzy information. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness.

Key words: intuitionistic fuzzy set, interval-valued intuitionistic fuzzy set, projection method, multiple attribute group decision making.

Zeng, Sh.; Baležentis, T.; Chen, Ji; Luo, G. 2013. A Projection method for multiple attribute group decision making with intuitionistic fuzzy informatikon, Informatica : International Journal 24(3): 485-503. [[IAOR (International Abstracts in Operations Research) INSPEC nuo 1990 MathSciNet [Current Mathematical Publications ir Mathematical Reviews] Science Citation Index Expanded (Web of Science) nuo 2002 (sąrašas) SCOPUS nuo 1996 VINITI Zentralblatt MATH]] [INSPEC bazė prieinama prenumeratoriams per EBSCO publishing].

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