Volume 12, Issue 2, 2019, Pages 1557 - 1574
2-Dimension Linguistic Bonferroni Mean Aggregation Operators and Their Application to Multiple Attribute Group Decision Making
Corresponding Author
Hua Zhu
Received 22 January 2019, Accepted 18 November 2019, Available Online 6 December 2019.
- DOI
- 10.2991/ijcis.d.191125.001How to use a DOI?
- Keywords
- MAGDM; Bonferroni mean operator; 2-dimension linguistic weight Bonferroni mean aggregation operator; 2-dimension linguistic variable; 2-dimension linguistic lattice implication algebra
- Abstract
The aim of this paper is to provide a multiple attribute group decision making (MAGDM) method based on the 2-dimension linguistic weight Bonferroni mean aggregation (2DLWBMA) operator. Firstly, the new operations of 2-dimension linguistic variables are defined. Then, the 2-dimension linguistic Bonferroni mean aggregation operator is proposed to describe the correlations of input arguments. Subsequently, the 2DLWBMA operator is investigated to consider the importance of attributes. Furthermore, a novel MAGDM method is introduced and two illustrative examples are given.
- Copyright
- © 2019 The Authors. Published by Atlantis Press SARL.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).
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TY - JOUR AU - Jianbin Zhao AU - Hua Zhu PY - 2019 DA - 2019/12/06 TI - 2-Dimension Linguistic Bonferroni Mean Aggregation Operators and Their Application to Multiple Attribute Group Decision Making JO - International Journal of Computational Intelligence Systems SP - 1557 EP - 1574 VL - 12 IS - 2 SN - 1875-6883 UR - https://doi.org/10.2991/ijcis.d.191125.001 DO - 10.2991/ijcis.d.191125.001 ID - Zhao2019 ER -