Multi/Many-Objective Particle Swarm Optimization Algorithm Based on Competition Mechanism

The recently proposed multiobjective particle swarm optimization algorithm based on competition mechanism algorithm cannot effectively deal with many-objective optimization problems, which is characterized by relatively poor convergence and diversity, and long computing runtime. In this paper, a nov...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Computational intelligence and neuroscience Ročník 2020; číslo 2020; s. 1 - 26
Hlavní autori: Zhang, Maosheng, Wang, Yi, Chen, Li, Yang, Wusi
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Cairo, Egypt Hindawi Publishing Corporation 2020
Hindawi
John Wiley & Sons, Inc
Predmet:
ISSN:1687-5265, 1687-5273, 1687-5273
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Abstract The recently proposed multiobjective particle swarm optimization algorithm based on competition mechanism algorithm cannot effectively deal with many-objective optimization problems, which is characterized by relatively poor convergence and diversity, and long computing runtime. In this paper, a novel multi/many-objective particle swarm optimization algorithm based on competition mechanism is proposed, which maintains population diversity by the maximum and minimum angle between ordinary and extreme individuals. And the recently proposed θ-dominance is adopted to further enhance the performance of the algorithm. The proposed algorithm is evaluated on the standard benchmark problems DTLZ, WFG, and UF1-9 and compared with the four recently proposed multiobjective particle swarm optimization algorithms and four state-of-the-art many-objective evolutionary optimization algorithms. The experimental results indicate that the proposed algorithm has better convergence and diversity, and its performance is superior to other comparative algorithms on most test instances.
AbstractList The recently proposed multiobjective particle swarm optimization algorithm based on competition mechanism algorithm cannot effectively deal with many-objective optimization problems, which is characterized by relatively poor convergence and diversity, and long computing runtime. In this paper, a novel multi/many-objective particle swarm optimization algorithm based on competition mechanism is proposed, which maintains population diversity by the maximum and minimum angle between ordinary and extreme individuals. And the recently proposed θ-dominance is adopted to further enhance the performance of the algorithm. The proposed algorithm is evaluated on the standard benchmark problems DTLZ, WFG, and UF1-9 and compared with the four recently proposed multiobjective particle swarm optimization algorithms and four state-of-the-art many-objective evolutionary optimization algorithms. The experimental results indicate that the proposed algorithm has better convergence and diversity, and its performance is superior to other comparative algorithms on most test instances.
The recently proposed multiobjective particle swarm optimization algorithm based on competition mechanism algorithm cannot effectively deal with many-objective optimization problems, which is characterized by relatively poor convergence and diversity, and long computing runtime. In this paper, a novel multi/many-objective particle swarm optimization algorithm based on competition mechanism is proposed, which maintains population diversity by the maximum and minimum angle between ordinary and extreme individuals. And the recently proposed -dominance is adopted to further enhance the performance of the algorithm. The proposed algorithm is evaluated on the standard benchmark problems DTLZ, WFG, and UF1-9 and compared with the four recently proposed multiobjective particle swarm optimization algorithms and four state-of-the-art many-objective evolutionary optimization algorithms. The experimental results indicate that the proposed algorithm has better convergence and diversity, and its performance is superior to other comparative algorithms on most test instances.
The recently proposed multiobjective particle swarm optimization algorithm based on competition mechanism algorithm cannot effectively deal with many-objective optimization problems, which is characterized by relatively poor convergence and diversity, and long computing runtime. In this paper, a novel multi/many-objective particle swarm optimization algorithm based on competition mechanism is proposed, which maintains population diversity by the maximum and minimum angle between ordinary and extreme individuals. And the recently proposed θ-dominance is adopted to further enhance the performance of the algorithm. The proposed algorithm is evaluated on the standard benchmark problems DTLZ, WFG, and UF1-9 and compared with the four recently proposed multiobjective particle swarm optimization algorithms and four state-of-the-art many-objective evolutionary optimization algorithms. The experimental results indicate that the proposed algorithm has better convergence and diversity, and its performance is superior to other comparative algorithms on most test instances.The recently proposed multiobjective particle swarm optimization algorithm based on competition mechanism algorithm cannot effectively deal with many-objective optimization problems, which is characterized by relatively poor convergence and diversity, and long computing runtime. In this paper, a novel multi/many-objective particle swarm optimization algorithm based on competition mechanism is proposed, which maintains population diversity by the maximum and minimum angle between ordinary and extreme individuals. And the recently proposed θ-dominance is adopted to further enhance the performance of the algorithm. The proposed algorithm is evaluated on the standard benchmark problems DTLZ, WFG, and UF1-9 and compared with the four recently proposed multiobjective particle swarm optimization algorithms and four state-of-the-art many-objective evolutionary optimization algorithms. The experimental results indicate that the proposed algorithm has better convergence and diversity, and its performance is superior to other comparative algorithms on most test instances.
The recently proposed multiobjective particle swarm optimization algorithm based on competition mechanism algorithm cannot effectively deal with many-objective optimization problems, which is characterized by relatively poor convergence and diversity, and long computing runtime. In this paper, a novel multi/many-objective particle swarm optimization algorithm based on competition mechanism is proposed, which maintains population diversity by the maximum and minimum angle between ordinary and extreme individuals. And the recently proposed θ -dominance is adopted to further enhance the performance of the algorithm. The proposed algorithm is evaluated on the standard benchmark problems DTLZ, WFG, and UF1-9 and compared with the four recently proposed multiobjective particle swarm optimization algorithms and four state-of-the-art many-objective evolutionary optimization algorithms. The experimental results indicate that the proposed algorithm has better convergence and diversity, and its performance is superior to other comparative algorithms on most test instances.
Audience Academic
Author Wang, Yi
Zhang, Maosheng
Yang, Wusi
Chen, Li
AuthorAffiliation 2 Key Laboratory for Geo-Hazards in Loess Area, MNR, Xi'an Center of Geological Survey, China Geological Survey, Xi'an 710054, China
1 School of Information Technology and Software, Northwest University, Xi'an 710127, China
AuthorAffiliation_xml – name: 2 Key Laboratory for Geo-Hazards in Loess Area, MNR, Xi'an Center of Geological Survey, China Geological Survey, Xi'an 710054, China
– name: 1 School of Information Technology and Software, Northwest University, Xi'an 710127, China
Author_xml – sequence: 1
  fullname: Zhang, Maosheng
– sequence: 2
  fullname: Wang, Yi
– sequence: 3
  fullname: Chen, Li
– sequence: 4
  fullname: Yang, Wusi
BackLink https://www.ncbi.nlm.nih.gov/pubmed/32190037$$D View this record in MEDLINE/PubMed
BookMark eNqFks1v0zAUwC00xLbCjTOKxAUJQv0R28kFqVTjQ1pVJODAyXKcl9ZVYneOs2n763HXboNJiINly-_3fn7We6foyHkHCL0k-D0hnE8ppnjKCaMlZk_QCRGlzDmV7Oj-LPgxOh2GDcZcckyfoWNGSYUxkyfo12Lsop0utLvOl_UGTLSXkH3TIVrTQfb9Soc-W26j7e2Njta7bNatfLBx3Wcf9QBNlq7mvt9CtLfhBZi1dnbon6Onre4GeHHYJ-jnp7Mf8y_5-fLz1_nsPDe8kDFvNKuJJIQCE00pC0lx3VYG17jWALJmlWBlU9eVANoUpJS8brikUjDS0ta0bII-7L3bse6hMeBi0J3aBtvrcK28turviLNrtfKXSuJkTvYJenMQBH8xwhBVbwcDXacd-HFQlMkKE84ETejrR-jGj8Gl7yVKVBQXuBAP1Ep3oKxrfXrX7KRqJiiVlKSVqFd_1n1f8F1vEkD3gAl-GAK0yth424Oks50iWO0GQO0GQB0GICW9e5R05_0H_naPr61r9JX9H30oGRIDrX6gCSulqNhvqtfGNw
CitedBy_id crossref_primary_10_1007_s00500_023_09050_7
crossref_primary_10_1007_s10489_022_03465_9
crossref_primary_10_1016_j_asoc_2020_106655
crossref_primary_10_3390_app11219787
crossref_primary_10_3390_math9161959
crossref_primary_10_1007_s40747_020_00263_z
crossref_primary_10_3390_app13063589
crossref_primary_10_7717_peerj_cs_2872
crossref_primary_10_3390_sym14122619
crossref_primary_10_1007_s11831_022_09778_9
crossref_primary_10_1109_ACCESS_2021_3086559
Cites_doi 10.1016/j.cie.2019.01.055
10.1109/TEVC.2013.2258025
10.1016/j.asoc.2019.01.033
10.1007/978-3-540-31880-4_35
10.1109/TEVC.2013.2281535
10.1007/s00500-016-2098-x
10.1155/2016/1898527
10.1016/j.swevo.2018.12.007
10.1109/TEVC.2004.826067
10.1016/j.ins.2016.09.026
10.1016/j.amc.2014.12.006
10.1007/s10489-018-1170-x
10.1109/TEVC.2007.892759
10.1109/TEVC.2012.2185847
10.1016/j.asoc.2016.11.009
10.1109/TEVC.2016.2631279
10.1109/TEVC.2015.2420112
10.1109/TEVC.2005.861417
10.1109/TCYB.2014.2322602
10.1162/EVCO_a_00009
10.1007/s00500-014-1570-8
10.1109/TEVC.2016.2519378
10.1016/j.ejor.2015.06.071
10.1109/TEVC.2016.2549267
10.1109/TEVC.2018.2791283
10.1162/EVCO_a_00104
10.1007/s00500-017-2687-3
10.1016/j.ins.2011.04.003
10.1016/j.ins.2017.10.037
10.1016/j.ins.2015.07.018
10.1109/TCYB.2017.2710133
10.1109/mci.2017.2742868
10.1109/tevc.2008.925798
10.1371/journal.pone.0172033
10.1109/4235.996017
ContentType Journal Article
Copyright Copyright © 2020 Wusi Yang et al.
COPYRIGHT 2020 John Wiley & Sons, Inc.
Copyright © 2020 Wusi Yang et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. http://creativecommons.org/licenses/by/4.0
Copyright © 2020 Wusi Yang et al. 2020
Copyright_xml – notice: Copyright © 2020 Wusi Yang et al.
– notice: COPYRIGHT 2020 John Wiley & Sons, Inc.
– notice: Copyright © 2020 Wusi Yang et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. http://creativecommons.org/licenses/by/4.0
– notice: Copyright © 2020 Wusi Yang et al. 2020
DBID ADJCN
AHFXO
RHU
RHW
RHX
AAYXX
CITATION
CGR
CUY
CVF
ECM
EIF
NPM
3V.
7QF
7QQ
7SC
7SE
7SP
7SR
7TA
7TB
7TK
7U5
7X7
7XB
8AL
8BQ
8FD
8FE
8FG
8FH
8FI
8FJ
8FK
ABJCF
ABUWG
AFKRA
ARAPS
AZQEC
BBNVY
BENPR
BGLVJ
BHPHI
CCPQU
CWDGH
DWQXO
F28
FR3
FYUFA
GHDGH
GNUQQ
H8D
H8G
HCIFZ
JG9
JQ2
K7-
K9.
KR7
L6V
L7M
LK8
L~C
L~D
M0N
M0S
M1P
M7P
M7S
P5Z
P62
PHGZM
PHGZT
PIMPY
PJZUB
PKEHL
PPXIY
PQEST
PQGLB
PQQKQ
PQUKI
PRINS
PSYQQ
PTHSS
Q9U
7X8
5PM
DOI 10.1155/2020/5132803
DatabaseName الدوريات العلمية والإحصائية - e-Marefa Academic and Statistical Periodicals
معرفة - المحتوى العربي الأكاديمي المتكامل - e-Marefa Academic Complete
Hindawi Publishing Complete
Hindawi Publishing Subscription Journals
Hindawi Publishing Open Access
CrossRef
Medline
MEDLINE
MEDLINE (Ovid)
MEDLINE
MEDLINE
PubMed
ProQuest Central (Corporate)
Aluminium Industry Abstracts
Ceramic Abstracts
Computer and Information Systems Abstracts
Corrosion Abstracts
Electronics & Communications Abstracts
Engineered Materials Abstracts
Materials Business File
Mechanical & Transportation Engineering Abstracts
Neurosciences Abstracts
Solid State and Superconductivity Abstracts
Health & Medical Collection
ProQuest Central (purchase pre-March 2016)
Computing Database (Alumni Edition)
METADEX
Technology Research Database
ProQuest SciTech Collection
ProQuest Technology Collection
ProQuest Natural Science Collection
ProQuest Hospital Collection
Hospital Premium Collection (Alumni Edition)
ProQuest Central (Alumni) (purchase pre-March 2016)
ProQuest Materials Science & Engineering Collection
ProQuest Central (Alumni)
ProQuest Central UK/Ireland
Advanced Technologies & Computer Science Collection
ProQuest Central Essentials
Biological Science Database (Proquest)
ProQuest Central
Technology collection
Natural Science Collection
ProQuest One Community College
Middle East & Africa Database
ProQuest Central
ANTE: Abstracts in New Technology & Engineering
Engineering Research Database
Health Research Premium Collection
Health Research Premium Collection (Alumni)
ProQuest Central Student
Aerospace Database
Copper Technical Reference Library
SciTech Premium Collection
Materials Research Database
ProQuest Computer Science Collection
Computer Science Database
ProQuest Health & Medical Complete (Alumni)
Civil Engineering Abstracts
ProQuest Engineering Collection
Advanced Technologies Database with Aerospace
Biological Sciences
Computer and Information Systems Abstracts – Academic
Computer and Information Systems Abstracts Professional
Computing Database
ProQuest Health & Medical Collection
PML(ProQuest Medical Library)
Biological Science Database
Engineering Database
Advanced Technologies & Aerospace Database
ProQuest Advanced Technologies & Aerospace Collection
ProQuest Central Premium
ProQuest One Academic
Publicly Available Content Database
ProQuest Health & Medical Research Collection
ProQuest One Academic Middle East (New)
ProQuest One Health & Nursing
ProQuest One Academic Eastern Edition (DO NOT USE)
ProQuest One Applied & Life Sciences
ProQuest One Academic (retired)
ProQuest One Academic UKI Edition
ProQuest Central China
ProQuest One Psychology
Engineering Collection
ProQuest Central Basic
MEDLINE - Academic
PubMed Central (Full Participant titles)
DatabaseTitle CrossRef
MEDLINE
Medline Complete
MEDLINE with Full Text
PubMed
MEDLINE (Ovid)
Publicly Available Content Database
Materials Research Database
ProQuest One Psychology
Computer Science Database
ProQuest Central Student
ProQuest Advanced Technologies & Aerospace Collection
ProQuest Central Essentials
ProQuest Computer Science Collection
Computer and Information Systems Abstracts
SciTech Premium Collection
ProQuest Central China
Materials Business File
ProQuest One Applied & Life Sciences
Engineered Materials Abstracts
Health Research Premium Collection
Natural Science Collection
Health & Medical Research Collection
Biological Science Collection
ProQuest Central (New)
Engineering Collection
ANTE: Abstracts in New Technology & Engineering
Advanced Technologies & Aerospace Collection
Engineering Database
Aluminium Industry Abstracts
ProQuest Biological Science Collection
ProQuest One Academic Eastern Edition
Electronics & Communications Abstracts
ProQuest Hospital Collection
ProQuest Technology Collection
Health Research Premium Collection (Alumni)
Ceramic Abstracts
Biological Science Database
Neurosciences Abstracts
ProQuest Hospital Collection (Alumni)
ProQuest Health & Medical Complete
ProQuest One Academic UKI Edition
Solid State and Superconductivity Abstracts
Engineering Research Database
ProQuest One Academic
ProQuest One Academic (New)
Technology Collection
Technology Research Database
Computer and Information Systems Abstracts – Academic
ProQuest One Academic Middle East (New)
Mechanical & Transportation Engineering Abstracts
ProQuest Health & Medical Complete (Alumni)
ProQuest Central (Alumni Edition)
ProQuest One Community College
ProQuest One Health & Nursing
ProQuest Natural Science Collection
ProQuest Central
Aerospace Database
Copper Technical Reference Library
ProQuest Health & Medical Research Collection
ProQuest Engineering Collection
Middle East & Africa Database
Health and Medicine Complete (Alumni Edition)
ProQuest Central Korea
Advanced Technologies Database with Aerospace
Civil Engineering Abstracts
ProQuest Computing
ProQuest Central Basic
ProQuest Computing (Alumni Edition)
ProQuest SciTech Collection
METADEX
Computer and Information Systems Abstracts Professional
Advanced Technologies & Aerospace Database
ProQuest Medical Library
Materials Science & Engineering Collection
Corrosion Abstracts
ProQuest Central (Alumni)
MEDLINE - Academic
DatabaseTitleList

Publicly Available Content Database
MEDLINE

MEDLINE - Academic
CrossRef
Database_xml – sequence: 1
  dbid: RHX
  name: Hindawi Publishing Open Access
  url: http://www.hindawi.com/journals/
  sourceTypes: Publisher
– sequence: 2
  dbid: NPM
  name: PubMed
  url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed
  sourceTypes: Index Database
– sequence: 3
  dbid: PIMPY
  name: Publicly Available Content Database
  url: http://search.proquest.com/publiccontent
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Anatomy & Physiology
EISSN 1687-5273
Editor Bibbo, Daniele
Editor_xml – sequence: 1
  givenname: Daniele
  surname: Bibbo
  fullname: Bibbo, Daniele
EndPage 26
ExternalDocumentID PMC7063896
A622721272
32190037
10_1155_2020_5132803
1138769
Genre Journal Article
GrantInformation_xml – fundername: Natural Science Foundation of Shaanxi Province
  grantid: 2018JM6029
– fundername: National Key Research and Development Program Projects of China
  grantid: 2018YFC1504700
GroupedDBID ---
0R~
188
24P
29F
2UF
2WC
4.4
53G
5GY
5VS
6J9
7X7
8FE
8FG
8FH
8FI
8FJ
8R4
8R5
AAFWJ
AAKPC
AAMMB
ABDBF
ABIVO
ABJCF
ABUWG
ACCMX
ACGFO
ACIWK
ACM
ACPRK
ACUHS
ADBBV
ADJCN
ADRAZ
AEFGJ
AENEX
AFKRA
AGXDD
AHFXO
AHMBA
AIDQK
AIDYY
ALMA_UNASSIGNED_HOLDINGS
AOIJS
ARAPS
AZQEC
BAWUL
BBNVY
BCNDV
BENPR
BGLVJ
BHPHI
BPHCQ
BVXVI
C1A
CCPQU
CS3
CWDGH
DIK
DWQXO
E3Z
EBD
EBS
EJD
EMOBN
ESX
F5P
FYUFA
GNUQQ
GX1
H13
HCIFZ
HMCUK
HYE
I-F
IAO
IHR
IL9
INR
K6V
K7-
KQ8
L6V
LK8
M1P
M48
M7P
M7S
MK~
O5R
O5S
OK1
OVT
P2P
P62
PGMZT
PHGZM
PHGZT
PIMPY
PJZUB
PPXIY
PQGLB
PQQKQ
PROAC
PSQYO
PSYQQ
PTHSS
PUEGO
Q2X
RHU
RNS
RPM
SV3
TR2
TUS
UKHRP
UZ4
~8M
3V.
AAJEY
AINHJ
GROUPED_DOAJ
ICD
INH
IPY
ITC
M0N
RHW
RHX
XH6
AAYXX
AFFHD
ALUQN
CITATION
CGR
CNMHZ
CUY
CVCKV
CVF
ECM
EIF
NPM
7QF
7QQ
7SC
7SE
7SP
7SR
7TA
7TB
7TK
7U5
7XB
8AL
8BQ
8FD
8FK
F28
FR3
H8D
H8G
JG9
JQ2
K9.
KR7
L7M
L~C
L~D
PKEHL
PQEST
PQUKI
PRINS
Q9U
7X8
5PM
ID FETCH-LOGICAL-c547t-da3b17112e36d874720bf9c0b0baee7b39638dbb96e2d41875bd5727631f2fcf3
IEDL.DBID RHX
ISICitedReferencesCount 8
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000518667700001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 1687-5265
1687-5273
IngestDate Tue Nov 04 01:55:06 EST 2025
Sun Sep 28 11:12:20 EDT 2025
Sat Nov 29 14:53:24 EST 2025
Tue Nov 11 10:56:45 EST 2025
Thu Apr 03 07:06:36 EDT 2025
Sat Nov 29 02:55:42 EST 2025
Tue Nov 18 21:45:44 EST 2025
Sun Jun 02 18:54:50 EDT 2024
Thu Sep 25 15:24:55 EDT 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 2020
Language English
License This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
http://creativecommons.org/licenses/by/4.0
Copyright © 2020 Wusi Yang et al.
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c547t-da3b17112e36d874720bf9c0b0baee7b39638dbb96e2d41875bd5727631f2fcf3
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
Academic Editor: Daniele Bibbo
ORCID 0000-0002-9550-9779
OpenAccessLink https://dx.doi.org/10.1155/2020/5132803
PMID 32190037
PQID 2369204046
PQPubID 237303
PageCount 26
ParticipantIDs pubmedcentral_primary_oai_pubmedcentral_nih_gov_7063896
proquest_miscellaneous_2379015362
proquest_journals_2369204046
gale_infotracmisc_A622721272
pubmed_primary_32190037
crossref_citationtrail_10_1155_2020_5132803
crossref_primary_10_1155_2020_5132803
hindawi_primary_10_1155_2020_5132803
emarefa_primary_1138769
PublicationCentury 2000
PublicationDate 2020-00-00
PublicationDateYYYYMMDD 2020-01-01
PublicationDate_xml – year: 2020
  text: 2020-00-00
PublicationDecade 2020
PublicationPlace Cairo, Egypt
PublicationPlace_xml – name: Cairo, Egypt
– name: United States
– name: New York
PublicationTitle Computational intelligence and neuroscience
PublicationTitleAlternate Comput Intell Neurosci
PublicationYear 2020
Publisher Hindawi Publishing Corporation
Hindawi
John Wiley & Sons, Inc
Publisher_xml – name: Hindawi Publishing Corporation
– name: Hindawi
– name: John Wiley & Sons, Inc
References 22
23
45
24
46
25
26
48
27
28
(32) 2001
30
10
11
12
34
13
14
15
38
17
39
18
19
1
2
4
5
6
7
9
40
41
20
21
43
References_xml – ident: 19
  doi: 10.1016/j.cie.2019.01.055
– ident: 14
  doi: 10.1109/TEVC.2013.2258025
– ident: 18
  doi: 10.1016/j.asoc.2019.01.033
– ident: 23
  doi: 10.1007/978-3-540-31880-4_35
– ident: 10
  doi: 10.1109/TEVC.2013.2281535
– ident: 15
  doi: 10.1007/s00500-016-2098-x
– ident: 40
  doi: 10.1155/2016/1898527
– ident: 5
  doi: 10.1016/j.swevo.2018.12.007
– ident: 22
  doi: 10.1109/TEVC.2004.826067
– ident: 39
  doi: 10.1016/j.ins.2016.09.026
– ident: 17
  doi: 10.1016/j.amc.2014.12.006
– ident: 1
  doi: 10.1007/s10489-018-1170-x
– ident: 4
  doi: 10.1109/TEVC.2007.892759
– ident: 12
  doi: 10.1109/TEVC.2012.2185847
– ident: 30
  doi: 10.1016/j.asoc.2016.11.009
– ident: 34
  doi: 10.1109/TEVC.2016.2631279
– ident: 28
  doi: 10.1109/TEVC.2015.2420112
– ident: 43
  doi: 10.1109/TEVC.2005.861417
– ident: 25
  doi: 10.1109/TCYB.2014.2322602
– ident: 7
  doi: 10.1162/EVCO_a_00009
– year: 2001
  ident: 32
– ident: 13
  doi: 10.1007/s00500-014-1570-8
– ident: 11
  doi: 10.1109/TEVC.2016.2519378
– ident: 24
  doi: 10.1016/j.ejor.2015.06.071
– ident: 45
  doi: 10.1109/TEVC.2016.2549267
– ident: 9
  doi: 10.1109/TEVC.2018.2791283
– ident: 21
  doi: 10.1162/EVCO_a_00104
– ident: 20
  doi: 10.1007/s00500-017-2687-3
– ident: 2
  doi: 10.1016/j.ins.2011.04.003
– ident: 27
  doi: 10.1016/j.ins.2017.10.037
– ident: 6
  doi: 10.1016/j.ins.2015.07.018
– ident: 38
  doi: 10.1109/TCYB.2017.2710133
– ident: 46
  doi: 10.1109/mci.2017.2742868
– ident: 48
  doi: 10.1109/tevc.2008.925798
– ident: 26
  doi: 10.1371/journal.pone.0172033
– ident: 41
  doi: 10.1109/4235.996017
SSID ssj0057502
Score 2.2751052
Snippet The recently proposed multiobjective particle swarm optimization algorithm based on competition mechanism algorithm cannot effectively deal with many-objective...
SourceID pubmedcentral
proquest
gale
pubmed
crossref
hindawi
emarefa
SourceType Open Access Repository
Aggregation Database
Index Database
Enrichment Source
Publisher
StartPage 1
SubjectTerms Algorithms
Comparative analysis
Competition
Computer Simulation
Convergence
Evolutionary algorithms
Mathematical optimization
Multiple objective analysis
Optimization algorithms
Particle swarm optimization
SummonAdditionalLinks – databaseName: Computer Science Database
  dbid: K7-
  link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1Lb9QwELagUIkLr1IILMhIhQuKNnFiOzmhpaJCgj4kQCqnyE92UZMtu1sq_j0zjrOliMeBWxSPYlvz-sYZzxCyo7wT2lqZljrjaWmETSulqpTn3mqnhSxMKOL6Th4cVMfH9VE8cFvGtMrBJgZDbecGz8jHrBA1A4krxcvTryl2jcK_q7GFxlVyLWcsRzl_K9PBEgMS6XMOBSgSloEfEt85x5g_G3MIxaqhXVZ0SZuuVfCg1iZ6c4rB8fnsdxD010zKn1zT3q3_3dRtcjOCUjrppegOueK6u2Rr0kFA3n6nz2lIEw3n71vkU7iyO94HI5Ie6i-9vaRHUQLp-3O1aOkhGKI23vCkk5PPMOdq2tJX4DIthVe7Aa2HbDG67_Dy8WzZ3iMf915_2H2Txv4MqeGlXKVWFTqXANhcIWwFcQnLtK9NpjOtnJO6QOW2WtfCMVvmEBlpywEviSL3zBtfbJONbt65B4R6p7zMa-VrDfFZ7qsagJdVVvFaKVtmCXkxsKgxsXg59tA4aUIQw3mDDG0iQxPybE192hft-APd_cjtC7K8AP9QJ2SE3G9Qy2EeAzpnmolgTGJFfJaQnSgV__j-aGB7E03DsrngeUKerodxAkx369z8DGkk4jQAF7DEXsLWExXgY7BqUELkJdlbE2DB8Msj3WwaCofLgE_Fw78v6xG5gZvoz5lGZGO1OHOPyXXzbTVbLp4EDfsBWSUrqw
  priority: 102
  providerName: ProQuest
Title Multi/Many-Objective Particle Swarm Optimization Algorithm Based on Competition Mechanism
URI https://search.emarefa.net/detail/BIM-1138769
https://dx.doi.org/10.1155/2020/5132803
https://www.ncbi.nlm.nih.gov/pubmed/32190037
https://www.proquest.com/docview/2369204046
https://www.proquest.com/docview/2379015362
https://pubmed.ncbi.nlm.nih.gov/PMC7063896
Volume 2020
WOSCitedRecordID wos000518667700001&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: PRVPQU
  databaseName: Advanced Technologies & Aerospace Database
  customDbUrl:
  eissn: 1687-5273
  dateEnd: 20250131
  omitProxy: false
  ssIdentifier: ssj0057502
  issn: 1687-5265
  databaseCode: P5Z
  dateStart: 20080101
  isFulltext: true
  titleUrlDefault: https://search.proquest.com/hightechjournals
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: Biological Science Database
  customDbUrl:
  eissn: 1687-5273
  dateEnd: 20250131
  omitProxy: false
  ssIdentifier: ssj0057502
  issn: 1687-5265
  databaseCode: M7P
  dateStart: 20080101
  isFulltext: true
  titleUrlDefault: http://search.proquest.com/biologicalscijournals
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: Computer Science Database
  customDbUrl:
  eissn: 1687-5273
  dateEnd: 20250131
  omitProxy: false
  ssIdentifier: ssj0057502
  issn: 1687-5265
  databaseCode: K7-
  dateStart: 20080101
  isFulltext: true
  titleUrlDefault: http://search.proquest.com/compscijour
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: Engineering Database
  customDbUrl:
  eissn: 1687-5273
  dateEnd: 20250131
  omitProxy: false
  ssIdentifier: ssj0057502
  issn: 1687-5265
  databaseCode: M7S
  dateStart: 20080101
  isFulltext: true
  titleUrlDefault: http://search.proquest.com
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: Health & Medical Collection
  customDbUrl:
  eissn: 1687-5273
  dateEnd: 20250131
  omitProxy: false
  ssIdentifier: ssj0057502
  issn: 1687-5265
  databaseCode: 7X7
  dateStart: 20080101
  isFulltext: true
  titleUrlDefault: https://search.proquest.com/healthcomplete
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: Middle East & Africa Database
  customDbUrl:
  eissn: 1687-5273
  dateEnd: 20250131
  omitProxy: false
  ssIdentifier: ssj0057502
  issn: 1687-5265
  databaseCode: CWDGH
  dateStart: 20080101
  isFulltext: true
  titleUrlDefault: https://search.proquest.com/middleeastafrica
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: ProQuest Central
  customDbUrl:
  eissn: 1687-5273
  dateEnd: 20250131
  omitProxy: false
  ssIdentifier: ssj0057502
  issn: 1687-5265
  databaseCode: BENPR
  dateStart: 20080101
  isFulltext: true
  titleUrlDefault: https://www.proquest.com/central
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: Publicly Available Content Database
  customDbUrl:
  eissn: 1687-5273
  dateEnd: 20250131
  omitProxy: false
  ssIdentifier: ssj0057502
  issn: 1687-5265
  databaseCode: PIMPY
  dateStart: 20080101
  isFulltext: true
  titleUrlDefault: http://search.proquest.com/publiccontent
  providerName: ProQuest
– providerCode: PRVWIB
  databaseName: Wiley Online Library Open Access
  customDbUrl:
  eissn: 1687-5273
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0057502
  issn: 1687-5265
  databaseCode: 24P
  dateStart: 20070101
  isFulltext: true
  titleUrlDefault: https://authorservices.wiley.com/open-science/open-access/browse-journals.html
  providerName: Wiley-Blackwell
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV3fb9MwELbYYBIvCBiMQKmMNHhBEflpJ4_dtGkI2kUbSB0vkR3bNGhJUdsx8d9z57iBDhC8WEl8iaOc7-675PyFkH1hNJNKcT-RQeonFVN-JkTmp6FRUkvG48qSuL7nk0k2neaFI0la_v4JH6IdpueQt0PWlCGr51aW4uQ9O5muHS4Ajq60kIG9INv7ur79xrkbkWdHNwI2RO-Jd2aYA1_Xf0KaNwsmf4lAx_fJPQcd6ajT9QNyS7cPye6ohbS5-U5fUVvMad-S75ILu7D2zRhM3T-VXzqvRgs3T-j5tVg09BTcRePWYdLR5ef5ol7NGnoAgU1ROHRoMbWt6aJjjUuE62XziHw8PvpweOK7vyj4VZrwla9ELEMOsErHTGWQPUSBNHkVyEAKrbmM0QSVlDnTkUpCyF-kSgHVsDg0kalM_Jhst_NWPyHUaGF4mAuTS8iiQpPlAI-UUCLNhVBJ4JHX6ydcVo5iHP90cVnaVCNNS9RH6fThkZe99NeOWuMvcntOWT_Fwhi8eO6RASqvRFuEcSqwjKocsSjiyFsfeWTfKfUf1x-sNV46A16WUczyCBxcwjzyou_GAbAordXzK5ThiKYAAsAtdhOkHyiGSIDcPh7hG1OnF0Ba782etp5Zem9uUSR7-n93_4zcxd3urdCAbK8WV_o5uVN9W9XLxZBs8Sm3bTYktw-OJsUZ7L3j_hCLXAvbnkNbpJ-gv3g7Li6G1rh-AOS_E_c
linkProvider Hindawi Publishing
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Lb9NAEB6VlgouvMrDEGCR2l6QFT937QOHkFJSNUkrUUQ5mV3vmgTVTklcov4pfiOz9tqliMepB26WPfJ67W9mvlnPzgBs8kxRISWzA-GEdpBSaUecR3boZlIoQZmfVkVch2w8jo6P48MV-N7shdFplY1NrAy1nKV6jbzr-TT2EHEBNRmU--p8ifHZ4tXeDn7MLc_bfXPUH9imhYCdhgErbcl94TLkFMqnMkLq7Dkii1NHOIIrxYSv8SeFiKnyZOAieRcyRJdOfTfzsjTz8b7bp19t3aVK_801LTuuwVpE4wg1aq3_YeftoLH9yH3qLEeKqqsLzzep9mGoVxmcbojBX9Q06DJOcF3lHA946xTWJzocX05_R3p_zd38yRnu3v7fXuMduGVoN-nVenIXVlRxDzZ6BS9n-TnZJlUibPWHYQM-VpuSuyM0k_aB-FJ7BHJodIy8W_J5Tg7Q1OZmDyvpnXzGMctJTl4jKZAET_WreKTKhyMjpbdXTxf5fXh_JfN-AKvFrFCPgGSKZ8yNeRYLjEDdLIqRWkoueRhzLgPHgpcNJJLUlGfXXUJOkipMC8NEAygxALJgq5U-rcuS_EHuoUHXhZjroweMLehotCXajuE4KVqVNOlRz2O65r9nwaZB4T_u32lglhjjt0guMGbBi_ayHkAn9BVqdqZlmGaiSJ_wEWtEtwP56EV1XSQL2CWstwK6JPrlK8V0UpVGZxUDp4___ljP4cbgaDRMhnvj_SdwU0-oXlXrwGo5P1NP4Xr6rZwu5s-MfhP4dNXq8QOBQop5
linkToPdf http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Lb9QwEB6VQhEXXuURWMBILRcUbZ52ckBoaVlRbbutBEjtKdixzS5qsmV3y6p_jV_H2HG2FPE49cAtSkZxnHwz840zngHY4FpRISXzExGkflJS6WecZ34aaimUoCwubRHXXTYcZoeH-cEKfG_3wpi0ytYmWkMtJ6VZI-9GMc0jRFxCu9qlRRxs91-ffPVNBynzp7Vtp9FAZKDOFhi-zV7tbOO33oyi_tsPW-9812HAL9OEzX3JYxEypBwqpjJDZh0FQudlIALBlWIiNvCUQuRURTIJkdsLmaLHp3GoI13qGO97Ba6iF06Njg2Y33oBZEFNviNFJTYl6Nuk-zQ16w1BN8UwMGtbdTl3uKYqjgd86R7WRiYwX4x_R39_zeL8yS32b_3PL_Q23HRknPQa7bkDK6q-C-u9ms8n1Rl5QWx6rP3vsA5Hdqtydw-Np78vvjR-ghw4zSPvF3xakX00wJXb2Up6x59xjvNRRd4gVZAET23ZKMVmyZE9ZTZdj2fVPfh4KZO8D6v1pFYPgWjFNQtzrnOBcWmosxwJp-SSpznnMgk8eNnCoyhd0XbTO-S4sMFbmhYGTIUDkwebS-mTpljJH-QeOKSdi4Ux-sXcg45BXmGsG45Toq0pix6NImY6AUQebDhE_uP-nRZyhTOJs-Icbx48X142A5g0v1pNTo0MM_wUSRU-YoPu5UAx-lZTLckDdgH3SwFTKP3ilXo8sgXTmeXl9NHfH-sZXEcFKHZ3hoPHcMPMp1lq68DqfHqqnsC18tt8PJs-tYpO4NNlK8IP9DKRqA
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=Multi%2FMany-Objective+Particle+Swarm+Optimization+Algorithm+Based+on+Competition+Mechanism&rft.jtitle=Computational+intelligence+and+neuroscience&rft.au=Zhang%2C+Maosheng&rft.au=Wang%2C+Yi&rft.au=Chen%2C+Li&rft.au=Yang%2C+Wusi&rft.date=2020&rft.pub=Hindawi+Publishing+Corporation&rft.issn=1687-5265&rft.eissn=1687-5273&rft.volume=2020&rft.issue=2020&rft.spage=1&rft.epage=26&rft_id=info:doi/10.1155%2F2020%2F5132803&rft.externalDBID=ADJCN&rft.externalDocID=1138769
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1687-5265&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1687-5265&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1687-5265&client=summon