Integer programming modeling on group decision making with incomplete hesitant fuzzy linguistic preference relations

Wu, P; Li, H; Merigo, JM; Zhou, L

Integer programming modeling on group decision making with incomplete hesitant fuzzy linguistic preference relations

Wu, P Li, H Merigo, JM Zhou, L

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Publisher:: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publication Type:: Journal Article
Citation:: IEEE Access, 2019, 7, pp. 136867-136881
Issue Date:: 2019-01-01

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Field	Value	Language
dc.contributor.author	Wu, P
dc.contributor.author	Li, H
dc.contributor.author	Merigo, JM
dc.contributor.author	Zhou, L
dc.date.accessioned	2021-02-23T12:08:20Z
dc.date.available	2021-02-23T12:08:20Z
dc.date.issued	2019-01-01
dc.identifier.citation	IEEE Access, 2019, 7, pp. 136867-136881
dc.identifier.issn	2169-3536
dc.identifier.issn	2169-3536
dc.identifier.uri	http://hdl.handle.net/10453/146346
dc.description.abstract	© 2013 IEEE. Complementing missing information and priority vector are of significance important aspects in group decision making (GDM) with incomplete hesitant fuzzy linguistic preference relations (HFLPRs). In this paper, an integer programming model is developed based on additive consistency to estimate missing values of incomplete HFLPRs by using additive consistency. Once the missing values are complemented, a mixed 0-1 programming model is established to derive the priority vectors from complete HFLPRs, in which the underlying idea of the mixed 0-1 programming model is the probability sampling in statistics and minimum deviation between the priority vector and HFLPR. In addition, we also propose a new GDM approach for incomplete HFLPRs by integrating the integer programming model and the mixed 0-1 programming model. Finally, two case studies and comparative analysis detail the application of the proposed models.
dc.language	English
dc.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation.ispartof	IEEE Access
dc.relation.isbasedon	10.1109/ACCESS.2019.2942412
dc.rights	© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.	en_US
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	08 Information and Computing Sciences, 09 Engineering, 10 Technology
dc.title	Integer programming modeling on group decision making with incomplete hesitant fuzzy linguistic preference relations
dc.type	Journal Article
utslib.citation.volume	7
utslib.for	08 Information and Computing Sciences
utslib.for	09 Engineering
utslib.for	10 Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Information, Systems and Modelling
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	open_access	*
dc.date.updated	2021-02-23T12:08:09Z
pubs.publication-status	Published
pubs.volume	7

Abstract:

© 2013 IEEE. Complementing missing information and priority vector are of significance important aspects in group decision making (GDM) with incomplete hesitant fuzzy linguistic preference relations (HFLPRs). In this paper, an integer programming model is developed based on additive consistency to estimate missing values of incomplete HFLPRs by using additive consistency. Once the missing values are complemented, a mixed 0-1 programming model is established to derive the priority vectors from complete HFLPRs, in which the underlying idea of the mixed 0-1 programming model is the probability sampling in statistics and minimum deviation between the priority vector and HFLPR. In addition, we also propose a new GDM approach for incomplete HFLPRs by integrating the integer programming model and the mixed 0-1 programming model. Finally, two case studies and comparative analysis detail the application of the proposed models.

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http://hdl.handle.net/10453/146346