Dynamic intuitionistic fuzzy multi-attribute decision making

نویسندگان

  • Zeshui Xu
  • Ronald R. Yager
چکیده

The dynamic multi-attribute decision making problems with intuitionistic fuzzy information are investigated. The notions of intuitionistic fuzzy variable and uncertain intuitionistic fuzzy variable are defined, and two new aggregation operators: dynamic intuitionistic fuzzy weighted averaging (DIFWA) operator and uncertain dynamic intuitionistic fuzzy weighted averaging (UDIFWA) operator are presented. Some methods, including the basic unit-interval monotonic (BUM) function based method, normal distribution based method, exponential distribution based method and average age method, are introduced to determine the weight vectors associated with these operators. A procedure based on the DIFWA operator is developed to solve the dynamic intuitionistic fuzzy multi-attribute decision making (DIF-MADM) problems where all the decision information about attribute values takes the form of intuitionistic fuzzy numbers collected at different periods, and a procedure based on the UDIFWA operator is developed for DIF-MADM under interval uncertainty in which all the decision information about attribute values takes the form of interval-valued intuitionistic fuzzy numbers collected at different periods. Finally, a practical case is used to illustrate the developed procedures. 2007 Elsevier Inc. All rights reserved.

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عنوان ژورنال:
  • Int. J. Approx. Reasoning

دوره 48  شماره 

صفحات  -

تاریخ انتشار 2008