کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
388102 | 660916 | 2012 | 9 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Some induced correlated aggregating operators with intuitionistic fuzzy information and their application to multiple attribute group decision making Some induced correlated aggregating operators with intuitionistic fuzzy information and their application to multiple attribute group decision making](/preview/png/388102.png)
In this paper, some multiple attribute group decision making (MAGDM) problems in which both the attribute weights and the expert weights are usually correlative, attribute values take the form of intuitionistic fuzzy values or interval-valued intuitionistic fuzzy values, are investigated. Firstly, some operational law, score function and accuracy function of intuitionistic fuzzy values or interval-valued intuitionistic fuzzy values are introduced. Then two new aggregation operators: induced intuitionistic fuzzy correlated averaging (I-IFCA) operator and induced intuitionistic fuzzy correlated geometric (I-IFCG) operator are developed and some desirable properties of the I-IFCA and I-IFCG operators are studied, such as commutativity, idempotency and monotonicity. An I-IFCA and IFCA (intuitionistic fuzzy correlated averaging) operators-based approach is developed to solve the MAGDM problems in which both the attribute weights and the expert weights usually correlative, attribute values take the form of intuitionistic fuzzy values. Then, we extend the developed models and procedures to the interval-valued intuitionistic fuzzy environment. Finally, some illustrative examples are given to verify the developed approach and to demonstrate its practicality and effectiveness.
► We investigate the intuitionistic fuzzy MAGDM problems with correlative weight information. The I-IFCA operator and I-IFCG operator are developed. An I-IFCA and IFCA operators-based approach is developed to solve the intuitionistic fuzzy MAGDM problems. Finally, we extend the developed models to the interval-valued intuitionistic fuzzy environment..
Journal: Expert Systems with Applications - Volume 39, Issue 2, 1 February 2012, Pages 2026–2034