TY - JOUR
T1 - Multiple Criteria Decision Making Based on Weighted Archimedean Power Partitioned Bonferroni Aggregation Operators of Generalised Orthopair Membership Grades
AU - Qin, Yuchu
AU - Qi, Qunfen
AU - Scott, Paul
AU - Jiang, Jane
N1 - Funding Information:
The authors are very grateful to the anonymous reviewers for their insightful comments to improve the paper. This study was funded by the EPSRC UKRI Innovation Fellowship (Ref. EP/S001328/1).
Publisher Copyright:
© 2020, The Author(s).
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/8/1
Y1 - 2020/8/1
N2 - In this paper, a multiple criteria decision making (MCDM) method based on weighted Archimedean power partitioned Bonferroni aggregation operators of generalised orthopair membership grades (GOMGs) is proposed. Bonferroni mean operator, geometric Bonferroni mean operator, power average operator, partitioned average operator, and Archimedean T-norm and T-conorm operations are introduced into generalised orthopair fuzzy sets to develop the Bonferroni aggregation operators. Their formal definitions are provided, and generalised and specific expressions are constructed. On the basis of the specific operators, a method for solving the MCDM problems based on GOMGs is designed. The working process, characteristics, and feasibility of the method are, respectively, demonstrated via a numerical example, a qualitative comparison at the aspect of characteristics, and a quantitative comparison using the example as benchmark. The demonstration results show that the proposed method is feasible that has desirable generality and flexibility in the aggregation of criterion values and concurrently has the capabilities to deal with the heterogeneous interrelationships of criteria, reduce the negative influence of biased criterion values, and capture the risk attitudes of decision makers.
AB - In this paper, a multiple criteria decision making (MCDM) method based on weighted Archimedean power partitioned Bonferroni aggregation operators of generalised orthopair membership grades (GOMGs) is proposed. Bonferroni mean operator, geometric Bonferroni mean operator, power average operator, partitioned average operator, and Archimedean T-norm and T-conorm operations are introduced into generalised orthopair fuzzy sets to develop the Bonferroni aggregation operators. Their formal definitions are provided, and generalised and specific expressions are constructed. On the basis of the specific operators, a method for solving the MCDM problems based on GOMGs is designed. The working process, characteristics, and feasibility of the method are, respectively, demonstrated via a numerical example, a qualitative comparison at the aspect of characteristics, and a quantitative comparison using the example as benchmark. The demonstration results show that the proposed method is feasible that has desirable generality and flexibility in the aggregation of criterion values and concurrently has the capabilities to deal with the heterogeneous interrelationships of criteria, reduce the negative influence of biased criterion values, and capture the risk attitudes of decision makers.
KW - Multiple criteria decision making
KW - Aggregation operator
KW - Generalised orthopair fuzzy set
KW - Bonferroni mean
KW - Geometric Bonferroni mean
KW - Archimedean T-norm and T-conorm
UR - http://www.scopus.com/inward/record.url?scp=85078597905&partnerID=8YFLogxK
U2 - 10.1007/s00500-020-04676-3
DO - 10.1007/s00500-020-04676-3
M3 - Article
VL - 24
SP - 12329
EP - 12355
JO - Soft Computing
JF - Soft Computing
SN - 1432-7643
IS - 16
ER -