Multiattribute Group Decision-Making Based on Linguistic Pythagorean Fuzzy Interaction Partitioned Bonferroni Mean Aggregation Operators

The partitioned Bonferroni mean (PBM) operator can efficiently aggregate inputs, which are divided into parts based on their interrelationships. To date, it has not been used to aggregate linguistic Pythagorean fuzzy numbers (LPFNs). In this paper, we extend the PBM operator and partitioned geometri...

Full description

Saved in:
Bibliographic Details
Main Authors: Mingwei Lin, Jiuhan Wei, Zeshui Xu, Riqing Chen
Format: Article
Language:English
Published: Wiley 2018-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2018/9531064
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850216868189569024
author Mingwei Lin
Jiuhan Wei
Zeshui Xu
Riqing Chen
author_facet Mingwei Lin
Jiuhan Wei
Zeshui Xu
Riqing Chen
author_sort Mingwei Lin
collection DOAJ
description The partitioned Bonferroni mean (PBM) operator can efficiently aggregate inputs, which are divided into parts based on their interrelationships. To date, it has not been used to aggregate linguistic Pythagorean fuzzy numbers (LPFNs). In this paper, we extend the PBM operator and partitioned geometric Bonferroni mean (PGBM) operator to the linguistic Pythagorean fuzzy sets (LPFSs) and use them to develop a novel multiattribute group decision-making model under the linguistic Pythagorean fuzzy environment. We first define some novel operational laws for LPFNs, which take into consideration the interactions between the membership degree (MD) and nonmembership degree (NMD) from two different LPFNs. Based on these novel operational laws, we put forward the interaction PBM (LPFIPBM) operator, the weighted interaction PBM (LPFWIPBM) operator, the interaction PGBM (LPFIPGBM) operator, and the weighted interaction PGBM (LPFWIPGBM) operator. Then, we study some properties of these proposed operators and discuss their special cases. Based on the proposed LPFWIPBM and LPFWIPGBM operators, a novel multiattribute group decision-making model is developed to process the linguistic Pythagorean fuzzy information. Finally, some illustrative examples are introduced to compare our proposed methods with the existing ones.
format Article
id doaj-art-2f3fb416143442d294cdbae9d13daad1
institution OA Journals
issn 1076-2787
1099-0526
language English
publishDate 2018-01-01
publisher Wiley
record_format Article
series Complexity
spelling doaj-art-2f3fb416143442d294cdbae9d13daad12025-08-20T02:08:12ZengWileyComplexity1076-27871099-05262018-01-01201810.1155/2018/95310649531064Multiattribute Group Decision-Making Based on Linguistic Pythagorean Fuzzy Interaction Partitioned Bonferroni Mean Aggregation OperatorsMingwei Lin0Jiuhan Wei1Zeshui Xu2Riqing Chen3College of Mathematics and Informatics, Fujian Normal University, Fuzhou, Fujian 350117, ChinaDigital Fujian Internet-of-Things Laboratory of Environmental Monitoring, Fujian Normal University, Fuzhou, Fujian 350117, ChinaBusiness School, Sichuan University, Chengdu, Sichuan 610064, ChinaDigital Fujian Institute of the Big Data for Agriculture and Forestry, Fujian Agriculture and Forestry University, Fuzhou, Fujian 350002, ChinaThe partitioned Bonferroni mean (PBM) operator can efficiently aggregate inputs, which are divided into parts based on their interrelationships. To date, it has not been used to aggregate linguistic Pythagorean fuzzy numbers (LPFNs). In this paper, we extend the PBM operator and partitioned geometric Bonferroni mean (PGBM) operator to the linguistic Pythagorean fuzzy sets (LPFSs) and use them to develop a novel multiattribute group decision-making model under the linguistic Pythagorean fuzzy environment. We first define some novel operational laws for LPFNs, which take into consideration the interactions between the membership degree (MD) and nonmembership degree (NMD) from two different LPFNs. Based on these novel operational laws, we put forward the interaction PBM (LPFIPBM) operator, the weighted interaction PBM (LPFWIPBM) operator, the interaction PGBM (LPFIPGBM) operator, and the weighted interaction PGBM (LPFWIPGBM) operator. Then, we study some properties of these proposed operators and discuss their special cases. Based on the proposed LPFWIPBM and LPFWIPGBM operators, a novel multiattribute group decision-making model is developed to process the linguistic Pythagorean fuzzy information. Finally, some illustrative examples are introduced to compare our proposed methods with the existing ones.http://dx.doi.org/10.1155/2018/9531064
spellingShingle Mingwei Lin
Jiuhan Wei
Zeshui Xu
Riqing Chen
Multiattribute Group Decision-Making Based on Linguistic Pythagorean Fuzzy Interaction Partitioned Bonferroni Mean Aggregation Operators
Complexity
title Multiattribute Group Decision-Making Based on Linguistic Pythagorean Fuzzy Interaction Partitioned Bonferroni Mean Aggregation Operators
title_full Multiattribute Group Decision-Making Based on Linguistic Pythagorean Fuzzy Interaction Partitioned Bonferroni Mean Aggregation Operators
title_fullStr Multiattribute Group Decision-Making Based on Linguistic Pythagorean Fuzzy Interaction Partitioned Bonferroni Mean Aggregation Operators
title_full_unstemmed Multiattribute Group Decision-Making Based on Linguistic Pythagorean Fuzzy Interaction Partitioned Bonferroni Mean Aggregation Operators
title_short Multiattribute Group Decision-Making Based on Linguistic Pythagorean Fuzzy Interaction Partitioned Bonferroni Mean Aggregation Operators
title_sort multiattribute group decision making based on linguistic pythagorean fuzzy interaction partitioned bonferroni mean aggregation operators
url http://dx.doi.org/10.1155/2018/9531064
work_keys_str_mv AT mingweilin multiattributegroupdecisionmakingbasedonlinguisticpythagoreanfuzzyinteractionpartitionedbonferronimeanaggregationoperators
AT jiuhanwei multiattributegroupdecisionmakingbasedonlinguisticpythagoreanfuzzyinteractionpartitionedbonferronimeanaggregationoperators
AT zeshuixu multiattributegroupdecisionmakingbasedonlinguisticpythagoreanfuzzyinteractionpartitionedbonferronimeanaggregationoperators
AT riqingchen multiattributegroupdecisionmakingbasedonlinguisticpythagoreanfuzzyinteractionpartitionedbonferronimeanaggregationoperators