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An Additive Consistency and Consensus Approach for Group Decision Making With Probabilistic Hesitant Fuzzy Linguistic Preference Relations and Its Application in Failure Criticality Analysis
In this article, probabilistic hesitant fuzzy linguistic preference relations (PHFLPRs) are proposed to present the qualitative pairwise preference information of decision makers (DMs) with hesitation and probability uncertainty assessments. The measurements and improvements of additive consistency...
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Published in: | IEEE transactions on cybernetics 2022-11, Vol.52 (11), p.12501-12513 |
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description | In this article, probabilistic hesitant fuzzy linguistic preference relations (PHFLPRs) are proposed to present the qualitative pairwise preference information of decision makers (DMs) with hesitation and probability uncertainty assessments. The measurements and improvements of additive consistency and consensus of PHFLPRs are investigated in group decision making (GDM). First, a new concept of probabilistic hesitant fuzzy linguistic term sets is defined. Second, the consistency and consensus measurements are established to survey the additive consistency and consensus levels of PHFLPRs. Subsequently, an optimization model is developed to improve the unacceptably additive consistent PHFLPR. By optimizing the unacceptable consensual PHFLPRs with repeating additive consistency improvement, the acceptably additive consistent and consensual PHFLPRs are obtained, based on which DMs' weights are determined objectively and then, the collective PHFLPR is aggregated from individual PHFLPRs. Alternatives' priority weights are derived from the collective PHFLPR as GDM. Finally, an example about failure criticality analysis is given, and a comparison analysis is presented. |
doi_str_mv | 10.1109/TCYB.2021.3072364 |
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(IEEE) 2022</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c293t-7cbb8733d5d89dec57a27cdc5104c8a44ff7b93fc9587b933846c7baec0bbccd3</citedby><cites>FETCH-LOGICAL-c293t-7cbb8733d5d89dec57a27cdc5104c8a44ff7b93fc9587b933846c7baec0bbccd3</cites><orcidid>0000-0002-1295-3031 ; 0000-0002-7820-1094</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9440782$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,54796</link.rule.ids></links><search><creatorcontrib>Wang, Zhichao</creatorcontrib><creatorcontrib>Ran, Yan</creatorcontrib><creatorcontrib>Jin, Chuanxi</creatorcontrib><creatorcontrib>Chen, Yifan</creatorcontrib><creatorcontrib>Zhang, Genbao</creatorcontrib><title>An Additive Consistency and Consensus Approach for Group Decision Making With Probabilistic Hesitant Fuzzy Linguistic Preference Relations and Its Application in Failure Criticality Analysis</title><title>IEEE transactions on cybernetics</title><addtitle>TCYB</addtitle><description>In this article, probabilistic hesitant fuzzy linguistic preference relations (PHFLPRs) are proposed to present the qualitative pairwise preference information of decision makers (DMs) with hesitation and probability uncertainty assessments. The measurements and improvements of additive consistency and consensus of PHFLPRs are investigated in group decision making (GDM). First, a new concept of probabilistic hesitant fuzzy linguistic term sets is defined. Second, the consistency and consensus measurements are established to survey the additive consistency and consensus levels of PHFLPRs. Subsequently, an optimization model is developed to improve the unacceptably additive consistent PHFLPR. By optimizing the unacceptable consensual PHFLPRs with repeating additive consistency improvement, the acceptably additive consistent and consensual PHFLPRs are obtained, based on which DMs' weights are determined objectively and then, the collective PHFLPR is aggregated from individual PHFLPRs. Alternatives' priority weights are derived from the collective PHFLPR as GDM. Finally, an example about failure criticality analysis is given, and a comparison analysis is presented.</description><subject>Additive consistency</subject><subject>Additives</subject><subject>consensus</subject><subject>Consistency</subject><subject>Decision making</subject><subject>Failure analysis</subject><subject>failure criticality analysis</subject><subject>Fuzzy sets</subject><subject>group decision making (GDM)</subject><subject>Indexes</subject><subject>Linguistics</subject><subject>Mathematical model</subject><subject>Optimization</subject><subject>Optimization models</subject><subject>probabilistic hesitant fuzzy linguistic preference relations (PHFLPRs)</subject><subject>Probabilistic logic</subject><subject>Statistical analysis</subject><subject>Uncertainty</subject><issn>2168-2267</issn><issn>2168-2275</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNo9UU1P3DAUtBAVIMoPQFye1PMu_khi5xgWdkHaqgiBqp4i58UppsHZ2k6l8OP62_DuInzx8_O8mbGHkHNG54zR8vJx8etqzilnc0ElF0V2QE44K9SMc5kfftaFPCZnIbzQtFRqleqIHIuMCpEX5Qn5Xzmo2tZG-8_AYnDBhmgcTqBduzsbF8YA1WbjB43P0A0eVn4YN3Bt0AY7OPiu_1j3G37a-Az3fmh0Y_vEYhFuTbBRuwjL8e1tgnWCjfube28645OQgQfT65h4wk7yLu7Eeou7JlgHS2370Sd3PrlE3ds4QeV0PyWvX8mXTvfBnH3sp-RpefO4uJ2tf6zuFtV6hrwUcSaxaZQUos1bVbYGc6m5xBZzRjNUOsu6Tjal6LDM1bYQKitQNtogbRrEVpySb3ve9A1_RxNi_TKMPpkINZe8YKwomEwotkehH0JIT6w33r5qP9WM1tvQ6m1o9Ta0-iO0NHOxn7HGmE98mWVUKi7eAVo4lhU</recordid><startdate>20221101</startdate><enddate>20221101</enddate><creator>Wang, Zhichao</creator><creator>Ran, Yan</creator><creator>Jin, Chuanxi</creator><creator>Chen, Yifan</creator><creator>Zhang, Genbao</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0002-1295-3031</orcidid><orcidid>https://orcid.org/0000-0002-7820-1094</orcidid></search><sort><creationdate>20221101</creationdate><title>An Additive Consistency and Consensus Approach for Group Decision Making With Probabilistic Hesitant Fuzzy Linguistic Preference Relations and Its Application in Failure Criticality Analysis</title><author>Wang, Zhichao ; Ran, Yan ; Jin, Chuanxi ; Chen, Yifan ; Zhang, Genbao</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c293t-7cbb8733d5d89dec57a27cdc5104c8a44ff7b93fc9587b933846c7baec0bbccd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Additive consistency</topic><topic>Additives</topic><topic>consensus</topic><topic>Consistency</topic><topic>Decision making</topic><topic>Failure analysis</topic><topic>failure criticality analysis</topic><topic>Fuzzy sets</topic><topic>group decision making (GDM)</topic><topic>Indexes</topic><topic>Linguistics</topic><topic>Mathematical model</topic><topic>Optimization</topic><topic>Optimization models</topic><topic>probabilistic hesitant fuzzy linguistic preference relations (PHFLPRs)</topic><topic>Probabilistic logic</topic><topic>Statistical analysis</topic><topic>Uncertainty</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Zhichao</creatorcontrib><creatorcontrib>Ran, Yan</creatorcontrib><creatorcontrib>Jin, Chuanxi</creatorcontrib><creatorcontrib>Chen, Yifan</creatorcontrib><creatorcontrib>Zhang, Genbao</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE/IET Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>IEEE transactions on cybernetics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Zhichao</au><au>Ran, Yan</au><au>Jin, Chuanxi</au><au>Chen, Yifan</au><au>Zhang, Genbao</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An Additive Consistency and Consensus Approach for Group Decision Making With Probabilistic Hesitant Fuzzy Linguistic Preference Relations and Its Application in Failure Criticality Analysis</atitle><jtitle>IEEE transactions on cybernetics</jtitle><stitle>TCYB</stitle><date>2022-11-01</date><risdate>2022</risdate><volume>52</volume><issue>11</issue><spage>12501</spage><epage>12513</epage><pages>12501-12513</pages><issn>2168-2267</issn><eissn>2168-2275</eissn><coden>ITCEB8</coden><abstract>In this article, probabilistic hesitant fuzzy linguistic preference relations (PHFLPRs) are proposed to present the qualitative pairwise preference information of decision makers (DMs) with hesitation and probability uncertainty assessments. The measurements and improvements of additive consistency and consensus of PHFLPRs are investigated in group decision making (GDM). First, a new concept of probabilistic hesitant fuzzy linguistic term sets is defined. Second, the consistency and consensus measurements are established to survey the additive consistency and consensus levels of PHFLPRs. Subsequently, an optimization model is developed to improve the unacceptably additive consistent PHFLPR. By optimizing the unacceptable consensual PHFLPRs with repeating additive consistency improvement, the acceptably additive consistent and consensual PHFLPRs are obtained, based on which DMs' weights are determined objectively and then, the collective PHFLPR is aggregated from individual PHFLPRs. Alternatives' priority weights are derived from the collective PHFLPR as GDM. Finally, an example about failure criticality analysis is given, and a comparison analysis is presented.</abstract><cop>Piscataway</cop><pub>IEEE</pub><pmid>34033569</pmid><doi>10.1109/TCYB.2021.3072364</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0002-1295-3031</orcidid><orcidid>https://orcid.org/0000-0002-7820-1094</orcidid></addata></record> |
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subjects | Additive consistency Additives consensus Consistency Decision making Failure analysis failure criticality analysis Fuzzy sets group decision making (GDM) Indexes Linguistics Mathematical model Optimization Optimization models probabilistic hesitant fuzzy linguistic preference relations (PHFLPRs) Probabilistic logic Statistical analysis Uncertainty |
title | An Additive Consistency and Consensus Approach for Group Decision Making With Probabilistic Hesitant Fuzzy Linguistic Preference Relations and Its Application in Failure Criticality Analysis |
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