Extended 2-tuple linguistic hybrid aggregation operators and their application to multi-attribute group decision making

DOI

10.1080/18756891.2013.874669How to use a DOI?

Keywords

multi-attribute group decision making, uncertain linguistic value, aggregation operator, TOPSIS method

Abstract

The aim of this paper is to develop some new 2-tuple linguistic hybrid aggregation operators, which are called the extended 2-tuple linguistic hybrid arithmetical weighted (ET-LHAW) operator, the extended 2-tuple linguistic hybrid geometric mean (ET-LHGM) operator, the induced ET-LHAW (IET-LHAW) operator and the induced ET-LHGM (IET-LHGM) operator. These operators do not only consider the importance of the elements but also reflect the importance of their ordered positions. Meantime, some desirable properties are studied, such as idempotency, boundary, etc. When the information about linguistic weight vectors is partly known, the models for the optimal linguistic weight vectors on an expert set, on an attribute set and on their ordered sets are established, respectively. Moreover, an approach to multi-attribute group decision making under linguistic environment is developed. Finally, a numerical example is offered to verify the developed method and to demonstrate its practicality and feasibility.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Fanyong Meng
AU  - Jie Tang
PY  - 2014
DA  - 2014/08/01
TI  - Extended 2-tuple linguistic hybrid aggregation operators and their application to multi-attribute group decision making
JO  - International Journal of Computational Intelligence Systems
SP  - 771
EP  - 784
VL  - 7
IS  - 4
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2013.874669
DO  - 10.1080/18756891.2013.874669
ID  - Meng2014
ER  -