Multiobjective Programming Approaches to Obtain the Priority Vectors under Uncertain Probabilistic Dual Hesitant Fuzzy Preference Environment

This paper develops uncertain probabilistic dual hesitant fuzzy numbers (UPDHFN), which includes six types of dual hesitant fuzzy sets (DHFNs). Next, the UPDHFN is applied to the uncertain probabilistic dual hesitant fuzzy preference relation (UPDHFPR). Furthermore, the (acceptable) expected consist...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:International journal of computational intelligence systems Ročník 14; číslo 1; s. 1189
Hlavní autori: Shao, Songtao, Zhang, Xiaohong
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Springer 01.01.2021
Predmet:
ISSN:1875-6883, 1875-6883
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Abstract This paper develops uncertain probabilistic dual hesitant fuzzy numbers (UPDHFN), which includes six types of dual hesitant fuzzy sets (DHFNs). Next, the UPDHFN is applied to the uncertain probabilistic dual hesitant fuzzy preference relation (UPDHFPR). Furthermore, the (acceptable) expected consistency, method of obtaining uncertain probabilistic information, and consistency-increasing iterative algorithm for flexible application of UPDHFPRs are explained respectively. Then, the UPDHFPRs and these approaches are applied to group decision-making procedure. Two operators are established to aggregate the UPDHFPRs and the integrated preference relations are also UPDHFPRs. In this model, due to the aggregated UPDHFPRs may be inconsistent. Thus an acceptable group consistency algorithm is designed. The group decision-making process is summarized under the UPDHFPR situation. Eventually, an illustrate example that selects the optimal alternative from three listed candidates is provided to verify our methods.
AbstractList This paper develops uncertain probabilistic dual hesitant fuzzy numbers (UPDHFN), which includes six types of dual hesitant fuzzy sets (DHFNs). Next, the UPDHFN is applied to the uncertain probabilistic dual hesitant fuzzy preference relation (UPDHFPR). Furthermore, the (acceptable) expected consistency, method of obtaining uncertain probabilistic information, and consistency-increasing iterative algorithm for flexible application of UPDHFPRs are explained respectively. Then, the UPDHFPRs and these approaches are applied to group decision-making procedure. Two operators are established to aggregate the UPDHFPRs and the integrated preference relations are also UPDHFPRs. In this model, due to the aggregated UPDHFPRs may be inconsistent. Thus an acceptable group consistency algorithm is designed. The group decision-making process is summarized under the UPDHFPR situation. Eventually, an illustrate example that selects the optimal alternative from three listed candidates is provided to verify our methods.
Author Shao, Songtao
Zhang, Xiaohong
Author_xml – sequence: 1
  givenname: Songtao
  surname: Shao
  fullname: Shao, Songtao
– sequence: 2
  givenname: Xiaohong
  surname: Zhang
  fullname: Zhang, Xiaohong
BookMark eNp9kc1uGyEURlGVSkmTvEBWvIDdyzDDwDJKkyZSqnSRdIv4uXawxmABjuS8Q9-52K6qqouuQPCdowvfJ3ISU0RCrhjMO6XY57Byocz9vGPAoZ8DsA_kjMlxmAkp-clf-1NyWcoKADrWA_T9Gfn5bTvVkOwKXQ1vSL_ntMxmvQ5xSa83m5yMe8VCa6JPtpoQaX3dh0LKoe7oj0alXOg2esz0JTrMh1CzWGPDFEoNjn7ZmoneYwnVxErvtu_vu5bABWZsBL2NbyGnuMZYL8jHhZkKXv5ez8nL3e3zzf3s8enrw83148zxYawzK7lwC4tOdMCZdcqrcdxf4YIpA90gBYIYpWfGu8E6rywfJQ5s7JUAgfycPBy9PpmV3uSwNnmnkwn6cJDyUpvcRp9Q98gsciUsB-y5HC1TXjChugGFAMubqzu6XE6ltGf98THQ-370oR_t9bEf3fppkPwHcu13WhGxZhOm_6G_AKXZnL8
CitedBy_id crossref_primary_10_3233_JIFS_233148
crossref_primary_10_1007_s40747_021_00497_5
crossref_primary_10_1155_2021_5522021
crossref_primary_10_1007_s41066_023_00397_8
crossref_primary_10_3390_axioms10030134
crossref_primary_10_1088_1742_6596_2442_1_012022
ContentType Journal Article
DBID AAYXX
CITATION
DOA
DOI 10.2991/ijcis.d.210304.001
DatabaseName CrossRef
DOAJ Directory of Open Access Journals
DatabaseTitle CrossRef
DatabaseTitleList
Database_xml – sequence: 1
  dbid: DOA
  name: DOAJ Open Access Full Text
  url: https://www.doaj.org/
  sourceTypes: Open Website
DeliveryMethod fulltext_linktorsrc
Discipline Computer Science
EISSN 1875-6883
ExternalDocumentID oai_doaj_org_article_4e1be396b30e4387b19d616925e660b3
10_2991_ijcis_d_210304_001
GroupedDBID 0R~
4.4
5GY
AAFWJ
AAJSJ
AAKKN
AASML
AAYXX
ABEEZ
ABFIM
ACACY
ACGFS
ACULB
ADBBV
ADCVX
ADMSI
AENEX
AFFHD
AFGXO
AFKRA
AFPKN
AHDSZ
ALMA_UNASSIGNED_HOLDINGS
AQTUD
ARAPS
ARCSS
AVBZW
BCNDV
BENPR
BGLVJ
C24
C6C
CCPQU
CITATION
CS3
DU5
EBLON
EBS
EJD
GROUPED_DOAJ
GTTXZ
H13
HCIFZ
HZ~
IL9
IPNFZ
J~4
K7-
M4Z
O9-
OK1
PHGZM
PHGZT
PQGLB
RIG
SOJ
TDBHL
TFL
TFW
TR2
ID FETCH-LOGICAL-c357t-b836cfbec62031bc9d977c357ef19a02586e0678d1adc5bcd9b378e51749606e3
IEDL.DBID DOA
ISICitedReferencesCount 6
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000657696200001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 1875-6883
IngestDate Fri Oct 03 12:44:03 EDT 2025
Sat Nov 29 02:36:52 EST 2025
Tue Nov 18 22:11:00 EST 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 1
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c357t-b836cfbec62031bc9d977c357ef19a02586e0678d1adc5bcd9b378e51749606e3
OpenAccessLink https://doaj.org/article/4e1be396b30e4387b19d616925e660b3
ParticipantIDs doaj_primary_oai_doaj_org_article_4e1be396b30e4387b19d616925e660b3
crossref_primary_10_2991_ijcis_d_210304_001
crossref_citationtrail_10_2991_ijcis_d_210304_001
PublicationCentury 2000
PublicationDate 2021-01-01
PublicationDateYYYYMMDD 2021-01-01
PublicationDate_xml – month: 01
  year: 2021
  text: 2021-01-01
  day: 01
PublicationDecade 2020
PublicationTitle International journal of computational intelligence systems
PublicationYear 2021
Publisher Springer
Publisher_xml – name: Springer
SSID ssj0002140044
Score 2.2563822
Snippet This paper develops uncertain probabilistic dual hesitant fuzzy numbers (UPDHFN), which includes six types of dual hesitant fuzzy sets (DHFNs). Next, the...
SourceID doaj
crossref
SourceType Open Website
Enrichment Source
Index Database
StartPage 1189
SubjectTerms Group decision-making
Multiplicative consistency
Preference relation
Priority vector
Uncertain probabilistic dual hesitant fuzzy number
Title Multiobjective Programming Approaches to Obtain the Priority Vectors under Uncertain Probabilistic Dual Hesitant Fuzzy Preference Environment
URI https://doaj.org/article/4e1be396b30e4387b19d616925e660b3
Volume 14
WOSCitedRecordID wos000657696200001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVAON
  databaseName: DOAJ Open Access Full Text
  customDbUrl:
  eissn: 1875-6883
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0002140044
  issn: 1875-6883
  databaseCode: DOA
  dateStart: 20080101
  isFulltext: true
  titleUrlDefault: https://www.doaj.org/
  providerName: Directory of Open Access Journals
– providerCode: PRVPQU
  databaseName: Computer Science Database
  customDbUrl:
  eissn: 1875-6883
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0002140044
  issn: 1875-6883
  databaseCode: K7-
  dateStart: 20140101
  isFulltext: true
  titleUrlDefault: http://search.proquest.com/compscijour
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: ProQuest Central (subscription)
  customDbUrl:
  eissn: 1875-6883
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0002140044
  issn: 1875-6883
  databaseCode: BENPR
  dateStart: 20140101
  isFulltext: true
  titleUrlDefault: https://www.proquest.com/central
  providerName: ProQuest
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV07T8MwELYQYmDhjXjLAxsK2E7i2COPVpWQoAMgtsivSK2gRX0gwX_gP3PnpFAWWFgyJJeT5Tv7fNbd9xFybHxVcW5DUuXSJJnwLNGIOKSYCZUKXOmQRbKJ4uZGPT7q7hzVF9aE1fDA9cSdZQE0pVralIUsVYXl2ksutciDlMxGnE9W6LlkCvdgwdE3s7pLBnZcftbru9741J8K5NVCxGz-IxLNAfbHyNJeIyvNkZCe10NZJwthsEFWZ3QLtFl9m-QjNssObb_eo2i3Lq16huBDzxto8DCmkyG9tZjwUzjbgVBviPx09CFez48pNo2N6D1ojLUAqMVGlF0EbKZXUxhJB7kCYMZpe_r-_gYSMzBa2vpui9si9-3W3WUnadgUEpfmxSSxKpWuApNJAQvZOu3h6IefQsW1gaOPkgFDl-fGu9w6r21aqIBI1pjlhHSbLA6Gg7BDqHQ5M84YA9lhxrlRgvtcC-YFE8FmbJfw2cyWroEaR8aLpxJSDrRGGa1R-rK2BhbW7ZKTr39eaqCNX6Uv0GBfkgiSHV-A65SN65R_uc7efyjZJ8sCy1zircwBWZyMpuGQLLnXSW88OopeCc_rIvkEglDqWw
linkProvider Directory of Open Access Journals
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Multiobjective+Programming+Approaches+to+Obtain+the+Priority+Vectors+under+Uncertain+Probabilistic+Dual+Hesitant+Fuzzy+Preference+Environment&rft.jtitle=International+journal+of+computational+intelligence+systems&rft.au=Shao%2C+Songtao&rft.au=Zhang%2C+Xiaohong&rft.date=2021-01-01&rft.issn=1875-6883&rft.eissn=1875-6883&rft.volume=14&rft.issue=1&rft.spage=1189&rft_id=info:doi/10.2991%2Fijcis.d.210304.001&rft.externalDBID=n%2Fa&rft.externalDocID=10_2991_ijcis_d_210304_001
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1875-6883&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1875-6883&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1875-6883&client=summon