4.7 Article

Some induced geometric aggregation operators with intuitionistic fuzzy information and their application to group decision making

Journal

APPLIED SOFT COMPUTING
Volume 10, Issue 2, Pages 423-431

Publisher

ELSEVIER
DOI: 10.1016/j.asoc.2009.08.009

Keywords

Intuitionistic fuzzy numbers; Interval-valued intuitionistic fuzzy numbers; Operational laws; Induced intuitionistic fuzzy ordered weighted geometric (I-IFOWG) operator; Induced interval-valued intuitionistic fuzzy ordered weighted geometric (I-IIFOWG) operator

Funding

  1. Science and Technology Research Foundation of Chongqing Education Commission [KJ091204]

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With respect to multiple attribute group decision making (MAGDM) problems in which both the attribute weights and the expert weights take the form of real numbers, attribute values take the form of intuitionistic fuzzy numbers or interval-valued intuitionistic fuzzy numbers, some new group decision making analysis methods are developed. Firstly, some operational laws, score function and accuracy function of intuitionistic fuzzy numbers or interval-valued intuitionistic fuzzy numbers are introduced. Then two new aggregation operators: induced intuitionistic fuzzy ordered weighted geometric (I-IFOWG) operator and induced interval-valued intuitionistic fuzzy ordered weighted geometric (I-IIFOWG) operator are proposed, and some desirable properties of the I-IFOWG and I-IIFOWG operators are studied, such as commutativity, idempotency and monotonicity. An I-IFOWG and IFWG (intuitionistic fuzzy weighted geometric) operators-based approach is developed to solve the MAGDM problems in which both the attribute weights and the expert weights take the form of real numbers, attribute values take the form of intuitionistic fuzzy numbers. Further, we extend the developed models and procedures based on I-IIFOWG and IIFWG (interval-valued intuitionistic fuzzy weighted geometric) operators to solve the MAGDM problems in which both the attribute weights and the expert weights take the form of real numbers, attribute values take the form of interval-valued intuitionistic fuzzy numbers. Finally, some illustrative examples are given to verify the developed approach and to demonstrate its practicality and effectiveness. (C) 2009 Elsevier B.V. All rights reserved.

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