Dombi Interval-Valued Hesitant Fuzzy Aggregation Operators for Information Security Risk Assessment
This paper studies the improved aggregation operator based on Dombi and its application in multiattribute decision making (MADM). Firstly, the axiomatic definition of interval-valued hesitant fuzzy elements (IVHFEs) based on Dombi t-norm and t-conorm is introduced. Secondly, we propose a series of I...
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Online Access: | http://dx.doi.org/10.1155/2020/3198645 |
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doaj-eb13b95427dc4139b20f9d7b4190598a2020-11-25T02:58:22ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472020-01-01202010.1155/2020/31986453198645Dombi Interval-Valued Hesitant Fuzzy Aggregation Operators for Information Security Risk AssessmentHao Bin Liu0Yi Liu1Lei Xu2Data Recovery Key Lab of Sichuan Province, Neijiang Normal University, Neijiang 641000, Sichuan, ChinaData Recovery Key Lab of Sichuan Province, Neijiang Normal University, Neijiang 641000, Sichuan, ChinaData Recovery Key Lab of Sichuan Province, Neijiang Normal University, Neijiang 641000, Sichuan, ChinaThis paper studies the improved aggregation operator based on Dombi and its application in multiattribute decision making (MADM). Firstly, the axiomatic definition of interval-valued hesitant fuzzy elements (IVHFEs) based on Dombi t-norm and t-conorm is introduced. Secondly, we propose a series of IVHFE aggregation operators (IVHFDWA, IVHFDWG, IVHFDOWA, IVHFDOWG, IVHFDHA, and IVHFDHG). In order to get the weight information of attributes, based on the basic idea of traditional distance formula, a distance formula between IVHFEs is constructed, and the optimization model of attribute weight is established. Then, a case study for selection of information security platform is given to demonstrate the merits of the developed method. The parameters of aggregation operator are analyzed in detail, and the critical value of parameters affecting decision making is given. Finally, this method is compared with other methods, which proves the validity and applicability of this method.http://dx.doi.org/10.1155/2020/3198645 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hao Bin Liu Yi Liu Lei Xu |
spellingShingle |
Hao Bin Liu Yi Liu Lei Xu Dombi Interval-Valued Hesitant Fuzzy Aggregation Operators for Information Security Risk Assessment Mathematical Problems in Engineering |
author_facet |
Hao Bin Liu Yi Liu Lei Xu |
author_sort |
Hao Bin Liu |
title |
Dombi Interval-Valued Hesitant Fuzzy Aggregation Operators for Information Security Risk Assessment |
title_short |
Dombi Interval-Valued Hesitant Fuzzy Aggregation Operators for Information Security Risk Assessment |
title_full |
Dombi Interval-Valued Hesitant Fuzzy Aggregation Operators for Information Security Risk Assessment |
title_fullStr |
Dombi Interval-Valued Hesitant Fuzzy Aggregation Operators for Information Security Risk Assessment |
title_full_unstemmed |
Dombi Interval-Valued Hesitant Fuzzy Aggregation Operators for Information Security Risk Assessment |
title_sort |
dombi interval-valued hesitant fuzzy aggregation operators for information security risk assessment |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2020-01-01 |
description |
This paper studies the improved aggregation operator based on Dombi and its application in multiattribute decision making (MADM). Firstly, the axiomatic definition of interval-valued hesitant fuzzy elements (IVHFEs) based on Dombi t-norm and t-conorm is introduced. Secondly, we propose a series of IVHFE aggregation operators (IVHFDWA, IVHFDWG, IVHFDOWA, IVHFDOWG, IVHFDHA, and IVHFDHG). In order to get the weight information of attributes, based on the basic idea of traditional distance formula, a distance formula between IVHFEs is constructed, and the optimization model of attribute weight is established. Then, a case study for selection of information security platform is given to demonstrate the merits of the developed method. The parameters of aggregation operator are analyzed in detail, and the critical value of parameters affecting decision making is given. Finally, this method is compared with other methods, which proves the validity and applicability of this method. |
url |
http://dx.doi.org/10.1155/2020/3198645 |
work_keys_str_mv |
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