New q-Rung Orthopair Hesitant Fuzzy Decision Making Based on Linear Programming and TOPSIS

A new multiple attribute decision making method based on the q-rung orthopair hesitant fuzzy sets has been developed. The evaluation values are given as q-rung orthopair hesitant fuzzy values. Then some weighted similarity functions are defined. A linear programming model is proposed to derive attri...

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Main Authors: Wei Yang, Yongfeng Pang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9286484/
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spelling doaj-4a4e1decddce4ceca90b7a32b212a4102021-03-30T04:43:15ZengIEEEIEEE Access2169-35362020-01-01822129922131110.1109/ACCESS.2020.30432559286484New q-Rung Orthopair Hesitant Fuzzy Decision Making Based on Linear Programming and TOPSISWei Yang0https://orcid.org/0000-0002-3483-9934Yongfeng Pang1https://orcid.org/0000-0002-4764-6699Department of Mathematics, School of Science, Xi’an University of Architecture and Technology, Xi’an, ChinaDepartment of Mathematics, School of Science, Xi’an University of Architecture and Technology, Xi’an, ChinaA new multiple attribute decision making method based on the q-rung orthopair hesitant fuzzy sets has been developed. The evaluation values are given as q-rung orthopair hesitant fuzzy values. Then some weighted similarity functions are defined. A linear programming model is proposed to derive attribute weights based on the similarity functions for the case of partly known attribute weight information and a formula is given to determine attribute weight based on similarity function and the Lagrange function for completely unknown attribute weights. Finally, TOPSIS method is used to rank alternatives. The application of the proposed approach is explored by the application of purchase self-service book sterilizer problem. Some comparisons are also conducted to demonstrate advantages of the proposed method.https://ieeexplore.ieee.org/document/9286484/Multiple attribute decision makingq-rung orthopair hesitant fuzzy setlinear programming modelTOPSISaggregation operator
collection DOAJ
language English
format Article
sources DOAJ
author Wei Yang
Yongfeng Pang
spellingShingle Wei Yang
Yongfeng Pang
New q-Rung Orthopair Hesitant Fuzzy Decision Making Based on Linear Programming and TOPSIS
IEEE Access
Multiple attribute decision making
q-rung orthopair hesitant fuzzy set
linear programming model
TOPSIS
aggregation operator
author_facet Wei Yang
Yongfeng Pang
author_sort Wei Yang
title New q-Rung Orthopair Hesitant Fuzzy Decision Making Based on Linear Programming and TOPSIS
title_short New q-Rung Orthopair Hesitant Fuzzy Decision Making Based on Linear Programming and TOPSIS
title_full New q-Rung Orthopair Hesitant Fuzzy Decision Making Based on Linear Programming and TOPSIS
title_fullStr New q-Rung Orthopair Hesitant Fuzzy Decision Making Based on Linear Programming and TOPSIS
title_full_unstemmed New q-Rung Orthopair Hesitant Fuzzy Decision Making Based on Linear Programming and TOPSIS
title_sort new q-rung orthopair hesitant fuzzy decision making based on linear programming and topsis
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2020-01-01
description A new multiple attribute decision making method based on the q-rung orthopair hesitant fuzzy sets has been developed. The evaluation values are given as q-rung orthopair hesitant fuzzy values. Then some weighted similarity functions are defined. A linear programming model is proposed to derive attribute weights based on the similarity functions for the case of partly known attribute weight information and a formula is given to determine attribute weight based on similarity function and the Lagrange function for completely unknown attribute weights. Finally, TOPSIS method is used to rank alternatives. The application of the proposed approach is explored by the application of purchase self-service book sterilizer problem. Some comparisons are also conducted to demonstrate advantages of the proposed method.
topic Multiple attribute decision making
q-rung orthopair hesitant fuzzy set
linear programming model
TOPSIS
aggregation operator
url https://ieeexplore.ieee.org/document/9286484/
work_keys_str_mv AT weiyang newqrungorthopairhesitantfuzzydecisionmakingbasedonlinearprogrammingandtopsis
AT yongfengpang newqrungorthopairhesitantfuzzydecisionmakingbasedonlinearprogrammingandtopsis
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