4.7 Article

Some geometric aggregation operators based on interval intuitionistic uncertain linguistic variables and their application to group decision making

期刊

APPLIED MATHEMATICAL MODELLING
卷 37, 期 4, 页码 2430-2444

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.apm.2012.05.032

关键词

The interval-valued intuitionistic uncertain linguistic variables; Multiple attribute group decision making; Weighted geometric average operator; Ordered weighted geometric operator; Hybrid geometric operator

资金

  1. Humanities and Social Sciences Research Project of Ministry of Education of China [10YJA630073, 09YJA630088]
  2. Natural Science Foundation of Shandong Province [ZR2011FM036]

向作者/读者索取更多资源

With respect to multiple attribute group decision making (MAGDM) problems in which both the attribute weights and the expert weights take the form of crisp numbers, and attribute values take the form of interval-valued intuitionistic uncertain linguistic variables, some new group decision making analysis methods are developed. Firstly, some operational laws, expected value and accuracy function of interval-valued intuitionistic uncertain linguistic variables are introduced. Then, an interval-valued intuitionistic uncertain linguistic weighted geometric average (IVIULWGA) operator and an interval-valued intuitionistic uncertain linguistic ordered weighted geometric (IVIULOWG) operator have been developed. Furthermore, some desirable properties of the IVIULWGA operator and the IVIULOWG operator, such as commutativity, idempotency and monotonicity, have been studied, and an interval-valued intuitionistic uncertain linguistic hybrid geometric (IVIULHG) operator which generalizes both the IVIULWGA operator and the IVIULOWG operator, was developed. Based on these operators, an approach to multiple attribute group decision making with interval-valued intuitionistic uncertain linguistic information has been proposed. Finally, an illustrative example is given to verify the developed approaches and to demonstrate their practicality and effectiveness. (c) 2012 Elsevier Inc. All rights reserved.

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