Set-Based Discrete Particle Swarm Optimization Based on Decomposition for Permutation-Based Multiobjective Combinatorial Optimization Problems

This paper studies a specific class of multiobjective combinatorial optimization problems (MOCOPs), namely the permutation-based MOCOPs. Many commonly seen MOCOPs, e.g., multiobjective traveling salesman problem (MOTSP), multiobjective project scheduling problem (MOPSP), belong to this problem class...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:IEEE transactions on cybernetics Ročník 48; číslo 7; s. 2139 - 2153
Hlavní autoři: Yu, Xue, Chen, Wei-Neng, Gu, Tianlong, Zhang, Huaxiang, Yuan, Huaqiang, Kwong, Sam, Zhang, Jun
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States IEEE 01.07.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
ISSN:2168-2267, 2168-2275, 2168-2275
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Abstract This paper studies a specific class of multiobjective combinatorial optimization problems (MOCOPs), namely the permutation-based MOCOPs. Many commonly seen MOCOPs, e.g., multiobjective traveling salesman problem (MOTSP), multiobjective project scheduling problem (MOPSP), belong to this problem class and they can be very different. However, as the permutation-based MOCOPs share the inherent similarity that the structure of their search space is usually in the shape of a permutation tree, this paper proposes a generic multiobjective set-based particle swarm optimization methodology based on decomposition, termed MS-PSO/D. In order to coordinate with the property of permutation-based MOCOPs, MS-PSO/D utilizes an element-based representation and a constructive approach. Through this, feasible solutions under constraints can be generated step by step following the permutation-tree-shaped structure. And problem-related heuristic information is introduced in the constructive approach for efficiency. In order to address the multiobjective optimization issues, the decomposition strategy is employed, in which the problem is converted into multiple single-objective subproblems according to a set of weight vectors. Besides, a flexible mechanism for diversity control is provided in MS-PSO/D. Extensive experiments have been conducted to study MS-PSO/D on two permutation-based MOCOPs, namely the MOTSP and the MOPSP. Experimental results validate that the proposed methodology is promising.
AbstractList This paper studies a specific class of multiobjective combinatorial optimization problems (MOCOPs), namely the permutation-based MOCOPs. Many commonly seen MOCOPs, e.g., multiobjective traveling salesman problem (MOTSP), multiobjective project scheduling problem (MOPSP), belong to this problem class and they can be very different. However, as the permutation-based MOCOPs share the inherent similarity that the structure of their search space is usually in the shape of a permutation tree, this paper proposes a generic multiobjective set-based particle swarm optimization methodology based on decomposition, termed MS-PSO/D. In order to coordinate with the property of permutation-based MOCOPs, MS-PSO/D utilizes an element-based representation and a constructive approach. Through this, feasible solutions under constraints can be generated step by step following the permutation-tree-shaped structure. And problem-related heuristic information is introduced in the constructive approach for efficiency. In order to address the multiobjective optimization issues, the decomposition strategy is employed, in which the problem is converted into multiple single-objective subproblems according to a set of weight vectors. Besides, a flexible mechanism for diversity control is provided in MS-PSO/D. Extensive experiments have been conducted to study MS-PSO/D on two permutation-based MOCOPs, namely the MOTSP and the MOPSP. Experimental results validate that the proposed methodology is promising.
This paper studies a specific class of multiobjective combinatorial optimization problems (MOCOPs), namely the permutation-based MOCOPs. Many commonly seen MOCOPs, e.g., multiobjective traveling salesman problem (MOTSP), multiobjective project scheduling problem (MOPSP), belong to this problem class and they can be very different. However, as the permutation-based MOCOPs share the inherent similarity that the structure of their search space is usually in the shape of a permutation tree, this paper proposes a generic multiobjective set-based particle swarm optimization methodology based on decomposition, termed MS-PSO/D. In order to coordinate with the property of permutation-based MOCOPs, MS-PSO/D utilizes an element-based representation and a constructive approach. Through this, feasible solutions under constraints can be generated step by step following the permutation-tree-shaped structure. And problem-related heuristic information is introduced in the constructive approach for efficiency. In order to address the multiobjective optimization issues, the decomposition strategy is employed, in which the problem is converted into multiple single-objective subproblems according to a set of weight vectors. Besides, a flexible mechanism for diversity control is provided in MS-PSO/D. Extensive experiments have been conducted to study MS-PSO/D on two permutation-based MOCOPs, namely the MOTSP and the MOPSP. Experimental results validate that the proposed methodology is promising.This paper studies a specific class of multiobjective combinatorial optimization problems (MOCOPs), namely the permutation-based MOCOPs. Many commonly seen MOCOPs, e.g., multiobjective traveling salesman problem (MOTSP), multiobjective project scheduling problem (MOPSP), belong to this problem class and they can be very different. However, as the permutation-based MOCOPs share the inherent similarity that the structure of their search space is usually in the shape of a permutation tree, this paper proposes a generic multiobjective set-based particle swarm optimization methodology based on decomposition, termed MS-PSO/D. In order to coordinate with the property of permutation-based MOCOPs, MS-PSO/D utilizes an element-based representation and a constructive approach. Through this, feasible solutions under constraints can be generated step by step following the permutation-tree-shaped structure. And problem-related heuristic information is introduced in the constructive approach for efficiency. In order to address the multiobjective optimization issues, the decomposition strategy is employed, in which the problem is converted into multiple single-objective subproblems according to a set of weight vectors. Besides, a flexible mechanism for diversity control is provided in MS-PSO/D. Extensive experiments have been conducted to study MS-PSO/D on two permutation-based MOCOPs, namely the MOTSP and the MOPSP. Experimental results validate that the proposed methodology is promising.
Author Chen, Wei-Neng
Yu, Xue
Yuan, Huaqiang
Zhang, Huaxiang
Kwong, Sam
Zhang, Jun
Gu, Tianlong
Author_xml – sequence: 1
  givenname: Xue
  surname: Yu
  fullname: Yu, Xue
  organization: School of Computer Science and Engineering, South China University of Technology, Guangzhou, China
– sequence: 2
  givenname: Wei-Neng
  orcidid: 0000-0003-0843-5802
  surname: Chen
  fullname: Chen, Wei-Neng
  email: cwnraul634@aliyun.com
  organization: School of Computer Science and Engineering, South China University of Technology, Guangzhou, China
– sequence: 3
  givenname: Tianlong
  surname: Gu
  fullname: Gu, Tianlong
  organization: School of Computer Science and Engineering, Guilin University of Electronic Technology, Guilin, China
– sequence: 4
  givenname: Huaxiang
  orcidid: 0000-0001-6259-7533
  surname: Zhang
  fullname: Zhang, Huaxiang
  organization: School of Information Science and Engineering, Shandong Normal University, Jinan, China
– sequence: 5
  givenname: Huaqiang
  surname: Yuan
  fullname: Yuan, Huaqiang
  organization: School of Computer Science and Network Security, Dongguan University of Technology, Dongguan, China
– sequence: 6
  givenname: Sam
  orcidid: 0000-0001-7484-7261
  surname: Kwong
  fullname: Kwong, Sam
  organization: Department of Computer Science, City University of Hong Kong, Hong Kong
– sequence: 7
  givenname: Jun
  orcidid: 0000-0001-7835-9871
  surname: Zhang
  fullname: Zhang, Jun
  email: junzhang@ieee.org
  organization: School of Computer Science and Engineering, South China University of Technology, Guangzhou, China
BackLink https://www.ncbi.nlm.nih.gov/pubmed/28792909$$D View this record in MEDLINE/PubMed
BookMark eNp9kc9u1DAQxi1UREvpAyAkFIkLlyz2OIntI93yTyrqSi0HTpbjTCSvknixnSJ4CJ4Zb7OtRA_44vHo930az_ecHE1-QkJeMrpijKp3N-vv5yugTKxAgGRAn5ATYI0sAUR99FA34picxbil-cjcUvIZOQYpFCiqTsifa0zluYnYFRcu2oAJi40JydkBi-ufJozF1S650f02yfmpWNBcXKD1485Hd9fufSg2GMY53WEHx6_zkF_tFm1yt1is_di6ySQfnBn-td0E3w44xhfkaW-GiGeH-5R8-_jhZv25vLz69GX9_rK0vFKpbDrBsZK2MpZh0_RY1dK2xlouABBr3gqGskbBO2kZh74H7FRTiV5Bx2rgp-Tt4rsL_seMMekx_x6HwUzo56iZAiF5LVSV0TeP0K2fw5Sn08BEVWeQ7anXB2puR-z0LrjRhF_6ftMZEAtgg48xYK-tW5aVgnGDZlTvY9X7WPU-Vn2INSvZI-W9-f80rxaNQ8QHXlLKuQT-F-tlr1s
CODEN ITCEB8
CitedBy_id crossref_primary_10_1016_j_ins_2023_119603
crossref_primary_10_1109_TCYB_2019_2925015
crossref_primary_10_1109_ACCESS_2019_2957637
crossref_primary_10_1007_s40998_025_00853_y
crossref_primary_10_1016_j_eswa_2020_113763
crossref_primary_10_1109_TEVC_2018_2878221
crossref_primary_10_1109_TIM_2021_3063190
crossref_primary_10_1016_j_asoc_2020_106382
crossref_primary_10_1016_j_jmapro_2020_04_085
crossref_primary_10_1016_j_swevo_2019_100607
crossref_primary_10_1109_TEVC_2024_3418470
crossref_primary_10_1109_JIOT_2024_3516121
crossref_primary_10_1007_s00500_020_05268_x
crossref_primary_10_1109_TNSE_2019_2932781
crossref_primary_10_1109_TCDS_2019_2944945
crossref_primary_10_3390_e26110968
crossref_primary_10_1109_TCYB_2021_3097312
crossref_primary_10_1007_s13042_023_02081_4
crossref_primary_10_1007_s40747_024_01465_5
crossref_primary_10_1016_j_ins_2018_07_035
crossref_primary_10_1109_TIM_2025_3551007
crossref_primary_10_1109_TCYB_2020_3022673
crossref_primary_10_1016_j_neunet_2024_106548
crossref_primary_10_1109_TVT_2019_2948953
crossref_primary_10_1016_j_trc_2021_103488
crossref_primary_10_1016_j_swevo_2025_102138
crossref_primary_10_1162_leon_a_02341
crossref_primary_10_1016_j_asoc_2020_106477
crossref_primary_10_1109_TCYB_2018_2834363
crossref_primary_10_1007_s11036_019_01403_7
crossref_primary_10_1016_j_asoc_2019_105490
crossref_primary_10_1080_09540091_2020_1841111
crossref_primary_10_1109_TCYB_2018_2811761
crossref_primary_10_1007_s00521_023_09290_6
crossref_primary_10_1109_TCYB_2018_2836388
crossref_primary_10_1109_TII_2018_2875048
crossref_primary_10_3233_IDA_205271
crossref_primary_10_1109_TMECH_2024_3396222
crossref_primary_10_1109_TCYB_2021_3103811
crossref_primary_10_1016_j_asoc_2022_109073
crossref_primary_10_1016_j_eswa_2023_120402
crossref_primary_10_1109_TSMC_2023_3239953
crossref_primary_10_3390_sym12020229
crossref_primary_10_1109_TSMC_2018_2861879
crossref_primary_10_1016_j_swevo_2024_101574
crossref_primary_10_1109_ACCESS_2021_3070634
crossref_primary_10_1016_j_engappai_2022_105249
crossref_primary_10_1109_TVT_2021_3109265
crossref_primary_10_1109_TCYB_2021_3101880
crossref_primary_10_1109_ACCESS_2020_2972123
crossref_primary_10_1109_TCYB_2020_2966492
crossref_primary_10_1109_TCYB_2018_2821180
crossref_primary_10_1109_TNSM_2023_3284206
crossref_primary_10_1016_j_swevo_2024_101722
crossref_primary_10_1109_ACCESS_2019_2926584
crossref_primary_10_1109_TSMC_2024_3389751
crossref_primary_10_1016_j_swevo_2021_100851
Cites_doi 10.1109/TEVC.2016.2591064
10.1109/TII.2012.2205390
10.1109/TEVC.2009.2030331
10.1007/s00170-007-1115-8
10.1109/TEVC.2010.2059031
10.1504/IJSOM.2013.052095
10.1007/s002910000046
10.1109/TSE.2012.17
10.1109/4235.996017
10.1109/TCYB.2015.2475174
10.1093/oso/9780195099713.001.0001
10.1109/TSMCA.2008.923086
10.1109/TSMCB.2012.2209115
10.1109/TSMCB.2006.887946
10.1109/TCYB.2014.2360923
10.1016/j.cor.2010.02.004
10.1155/2015/189832
10.1109/TCYB.2013.2295886
10.1016/j.omega.2013.07.004
10.1109/TSMCC.2012.2188285
10.1145/2739480.2754702
10.1016/j.swevo.2011.03.001
10.1109/TEVC.2014.2315442
10.1016/j.cor.2015.04.009
10.1109/TSMCB.2012.2219859
10.1007/BF02578918
10.1109/CEC.2012.6256616
10.1016/S0377-2217(96)00170-1
10.1007/s10489-006-6926-z
10.1016/j.ejor.2007.10.054
10.1109/TCYB.2015.2409837
10.1109/TEVC.2010.2051446
10.1109/TSMCB.2012.2231860
10.1016/j.tcs.2005.05.020
10.1109/TSMCC.2011.2148712
10.1109/TEVC.2013.2281533
10.1109/TEVC.2007.892759
10.1007/978-3-540-72584-8_40
10.1109/TEVC.2012.2185702
10.1109/TCYB.2014.2360752
10.1109/TIE.2014.2314075
10.1109/TCYB.2016.2616170
10.1109/TEVC.2003.810758
10.1016/j.swevo.2013.11.001
10.1109/TEVC.2013.2260862
10.1109/TEVC.2013.2283916
10.1016/j.asoc.2010.04.001
10.1109/TEVC.2015.2501315
10.1021/ie000400v
10.1109/TSMCC.2009.2027335
10.1109/TEVC.2011.2166159
10.1109/TCYB.2013.2279211
10.1109/TEVC.2014.2350995
10.1109/TEVC.2011.2173577
10.1080/0305215X.2012.658782
10.1162/EVCO_a_00104
10.1137/S1052623496307510
10.1162/EVCO_a_00109
10.1109/TEVC.2015.2511142
10.1016/j.cie.2007.08.003
10.1109/TEVC.2002.802450
10.1109/TEVC.2003.810752
10.1155/2012/879614
10.1109/TEVC.2010.2077298
ContentType Journal Article
Copyright Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2018
Copyright_xml – notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2018
DBID 97E
ESBDL
RIA
RIE
AAYXX
CITATION
NPM
7SC
7SP
7TB
8FD
F28
FR3
H8D
JQ2
L7M
L~C
L~D
7X8
DOI 10.1109/TCYB.2017.2728120
DatabaseName IEEE Xplore (IEEE)
IEEE Xplore Open Access (Activated by CARLI)
IEEE All-Society Periodicals Package (ASPP) 1998–Present
IEEE Electronic Library (IEL)
CrossRef
PubMed
Computer and Information Systems Abstracts
Electronics & Communications Abstracts
Mechanical & Transportation Engineering Abstracts
Technology Research Database
ANTE: Abstracts in New Technology & Engineering
Engineering Research Database
Aerospace Database
ProQuest Computer Science Collection
Advanced Technologies Database with Aerospace
Computer and Information Systems Abstracts – Academic
Computer and Information Systems Abstracts Professional
MEDLINE - Academic
DatabaseTitle CrossRef
PubMed
Aerospace Database
Technology Research Database
Computer and Information Systems Abstracts – Academic
Mechanical & Transportation Engineering Abstracts
Electronics & Communications Abstracts
ProQuest Computer Science Collection
Computer and Information Systems Abstracts
Engineering Research Database
Advanced Technologies Database with Aerospace
ANTE: Abstracts in New Technology & Engineering
Computer and Information Systems Abstracts Professional
MEDLINE - Academic
DatabaseTitleList Aerospace Database
MEDLINE - Academic
PubMed

Database_xml – sequence: 1
  dbid: NPM
  name: PubMed
  url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed
  sourceTypes: Index Database
– sequence: 2
  dbid: RIE
  name: IEEE Electronic Library (IEL)
  url: https://ieeexplore.ieee.org/
  sourceTypes: Publisher
– sequence: 3
  dbid: 7X8
  name: MEDLINE - Academic
  url: https://search.proquest.com/medline
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Sciences (General)
Computer Science
EISSN 2168-2275
EndPage 2153
ExternalDocumentID 28792909
10_1109_TCYB_2017_2728120
8003382
Genre orig-research
Journal Article
GrantInformation_xml – fundername: Natural Science Foundation of Guangdong
  grantid: 2015A030306024
  funderid: 10.13039/501100003453
– fundername: “Guangdong Special Support Program”
  grantid: 2014TQ01X550
– fundername: National Natural Science Foundation of China
  grantid: 61622206; 61379061; 61332002
  funderid: 10.13039/501100001809
GroupedDBID 0R~
4.4
6IK
97E
AAJGR
AARMG
AASAJ
AAWTH
ABAZT
ABQJQ
ABVLG
ACIWK
AENEX
AGQYO
AGSQL
AHBIQ
AKJIK
AKQYR
ALMA_UNASSIGNED_HOLDINGS
ATWAV
BEFXN
BFFAM
BGNUA
BKEBE
BPEOZ
EBS
EJD
ESBDL
HZ~
IFIPE
IPLJI
JAVBF
M43
O9-
OCL
PQQKQ
RIA
RIE
RNS
AAYXX
CITATION
NPM
RIG
7SC
7SP
7TB
8FD
F28
FR3
H8D
JQ2
L7M
L~C
L~D
7X8
ID FETCH-LOGICAL-c349t-6d73e48c4ac1e66fe458cbacc3722ee53b71e85e73d8c132ff2ed9647f92d1523
IEDL.DBID RIE
ISICitedReferencesCount 69
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000435342100016&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 2168-2267
2168-2275
IngestDate Sat Sep 27 22:47:28 EDT 2025
Mon Jun 30 05:22:25 EDT 2025
Thu Jan 02 23:09:29 EST 2025
Sat Nov 29 06:48:35 EST 2025
Tue Nov 18 22:35:34 EST 2025
Wed Aug 27 02:50:51 EDT 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 7
Language English
License https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c349t-6d73e48c4ac1e66fe458cbacc3722ee53b71e85e73d8c132ff2ed9647f92d1523
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ORCID 0000-0001-7484-7261
0000-0001-7835-9871
0000-0001-6259-7533
0000-0003-0843-5802
OpenAccessLink https://ieeexplore.ieee.org/document/8003382
PMID 28792909
PQID 2174527814
PQPubID 85422
PageCount 15
ParticipantIDs crossref_citationtrail_10_1109_TCYB_2017_2728120
ieee_primary_8003382
pubmed_primary_28792909
proquest_miscellaneous_1927835794
proquest_journals_2174527814
crossref_primary_10_1109_TCYB_2017_2728120
PublicationCentury 2000
PublicationDate 2018-07-01
PublicationDateYYYYMMDD 2018-07-01
PublicationDate_xml – month: 07
  year: 2018
  text: 2018-07-01
  day: 01
PublicationDecade 2010
PublicationPlace United States
PublicationPlace_xml – name: United States
– name: Piscataway
PublicationTitle IEEE transactions on cybernetics
PublicationTitleAbbrev TCYB
PublicationTitleAlternate IEEE Trans Cybern
PublicationYear 2018
Publisher IEEE
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher_xml – name: IEEE
– name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
References ref57
ref13
ref56
ref12
ref59
ref15
ref58
ref14
ref53
ref52
ref55
ref11
ref54
ref10
ref16
ref19
ref18
ref51
ref50
(ref76) 2017
ref46
ref45
chávez (ref23) 2016; 7
ref47
ref41
ref44
miettinen (ref64) 1999
ref8
ref7
ref9
ref4
ref5
ref40
cai (ref3) 2015; 19
kumar (ref43) 2010; 2
ref35
coello (ref71) 2004
ref37
ref36
ref75
ref31
ref30
lin (ref6) 2016; 20
ref77
ref33
ref32
back (ref42) 1996
ref2
(ref70) 2017
ref39
(ref74) 2017
ref73
ref72
shukla (ref66) 2007
ref68
ref24
ref67
ref26
ref69
ref25
ref20
ref63
ref22
ref65
ref21
kennedy (ref48) 2011
ref28
ref27
schrijver (ref1) 2003
jia (ref49) 0
ref29
xiao (ref17) 2015
shi (ref34) 2004; 2
ref60
ref62
selvi (ref38) 2010; 5
ref61
References_xml – ident: ref54
  doi: 10.1109/TEVC.2016.2591064
– ident: ref52
  doi: 10.1109/TII.2012.2205390
– ident: ref33
  doi: 10.1109/TEVC.2009.2030331
– ident: ref30
  doi: 10.1007/s00170-007-1115-8
– ident: ref45
  doi: 10.1109/TEVC.2010.2059031
– volume: 5
  start-page: 1
  year: 2010
  ident: ref38
  article-title: Comparative analysis of ant colony and particle swarm optimization techniques
  publication-title: Int J Comput Appl
– ident: ref77
  doi: 10.1504/IJSOM.2013.052095
– year: 0
  ident: ref49
  article-title: A dynamic logistic dispatching system with set-based particle swarm optimization
  publication-title: IEEE Trans Syst Man Cybern Syst
– ident: ref2
  doi: 10.1007/s002910000046
– ident: ref56
  doi: 10.1109/TSE.2012.17
– ident: ref31
  doi: 10.1109/4235.996017
– ident: ref35
  doi: 10.1109/TCYB.2015.2475174
– year: 1996
  ident: ref42
  publication-title: Evolutionary Algorithms in Theory and Practice Evolution Strategies Evolutionary Programming Genetic Algorithms
  doi: 10.1093/oso/9780195099713.001.0001
– ident: ref29
  doi: 10.1109/TSMCA.2008.923086
– ident: ref7
  doi: 10.1109/TSMCB.2012.2209115
– ident: ref27
  doi: 10.1109/TSMCB.2006.887946
– ident: ref5
  doi: 10.1109/TCYB.2014.2360923
– ident: ref41
  doi: 10.1016/j.cor.2010.02.004
– ident: ref25
  doi: 10.1155/2015/189832
– ident: ref60
  doi: 10.1109/TCYB.2013.2295886
– ident: ref26
  doi: 10.1016/j.omega.2013.07.004
– ident: ref11
  doi: 10.1109/TSMCC.2012.2188285
– start-page: 759
  year: 2015
  ident: ref17
  article-title: Empirical study of multi-objective ant colony optimization to software project scheduling problems
  publication-title: Proc GECCO
  doi: 10.1145/2739480.2754702
– start-page: 688
  year: 2004
  ident: ref71
  article-title: A study of the parallelization of a coevolutionary multi-objective evolutionary algorithm
  publication-title: Proceedings of MICAI
– ident: ref39
  doi: 10.1016/j.swevo.2011.03.001
– ident: ref4
  doi: 10.1109/TEVC.2014.2315442
– volume: 2
  start-page: 8
  year: 2004
  ident: ref34
  article-title: Particle swarm optimization
  publication-title: IEEE Neural Networks Society
– ident: ref20
  doi: 10.1016/j.cor.2015.04.009
– ident: ref55
  doi: 10.1109/TSMCB.2012.2219859
– ident: ref10
  doi: 10.1007/BF02578918
– ident: ref16
  doi: 10.1109/CEC.2012.6256616
– ident: ref75
  doi: 10.1016/S0377-2217(96)00170-1
– ident: ref22
  doi: 10.1007/s10489-006-6926-z
– ident: ref14
  doi: 10.1016/j.ejor.2007.10.054
– year: 1999
  ident: ref64
  publication-title: Nonlinear Multiobjective Optimization
– ident: ref21
  doi: 10.1109/TCYB.2015.2409837
– ident: ref9
  doi: 10.1109/TEVC.2010.2051446
– year: 2017
  ident: ref76
  publication-title: Project Scheduling Problem Library-PSPLIB
– ident: ref13
  doi: 10.1109/TSMCB.2012.2231860
– ident: ref53
  doi: 10.1016/j.tcs.2005.05.020
– volume: 2
  start-page: 451
  year: 2010
  ident: ref43
  article-title: Genetic algorithm: Review and application
  publication-title: Int J Inf Technol Knowl Manag
– ident: ref51
  doi: 10.1109/TSMCC.2011.2148712
– ident: ref59
  doi: 10.1109/TEVC.2013.2281533
– ident: ref32
  doi: 10.1109/TEVC.2007.892759
– start-page: 310
  year: 2007
  ident: ref66
  article-title: On the normal boundary intersection method for generation of efficient front
  publication-title: Computational Science-ICCS 2007
  doi: 10.1007/978-3-540-72584-8_40
– ident: ref58
  doi: 10.1109/TEVC.2012.2185702
– ident: ref47
  doi: 10.1109/TCYB.2014.2360752
– ident: ref50
  doi: 10.1109/TIE.2014.2314075
– ident: ref37
  doi: 10.1109/TCYB.2016.2616170
– ident: ref72
  doi: 10.1109/TEVC.2003.810758
– ident: ref12
  doi: 10.1016/j.swevo.2013.11.001
– year: 2017
  ident: ref70
  publication-title: Traveling Salesman Problem Library-TSPLIB
– ident: ref63
  doi: 10.1109/TEVC.2013.2260862
– ident: ref18
  doi: 10.1109/TEVC.2013.2283916
– ident: ref19
  doi: 10.1016/j.asoc.2010.04.001
– ident: ref8
  doi: 10.1109/TEVC.2015.2501315
– ident: ref67
  doi: 10.1021/ie000400v
– volume: 7
  start-page: 35
  year: 2016
  ident: ref23
  article-title: A multi-objective Pareto ant colony algorithm for the multi-depot vehicle routing problem with backhauls
  publication-title: Int J Ind Eng Comput
– start-page: 760
  year: 2011
  ident: ref48
  article-title: Particle swarm optimization
  publication-title: Encyclopedia of Machine Learning
– ident: ref40
  doi: 10.1109/TSMCC.2009.2027335
– ident: ref62
  doi: 10.1109/TEVC.2011.2166159
– ident: ref46
  doi: 10.1109/TCYB.2013.2279211
– year: 2017
  ident: ref74
  publication-title: Professor Qingfu Zhang
– volume: 19
  start-page: 508
  year: 2015
  ident: ref3
  article-title: An external archive guided multiobjective evolutionary algorithm based on decomposition for combinatorial optimization
  publication-title: IEEE Trans Evol Comput
  doi: 10.1109/TEVC.2014.2350995
– ident: ref36
  doi: 10.1109/TEVC.2011.2173577
– ident: ref15
  doi: 10.1080/0305215X.2012.658782
– ident: ref61
  doi: 10.1162/EVCO_a_00104
– ident: ref65
  doi: 10.1137/S1052623496307510
– ident: ref68
  doi: 10.1162/EVCO_a_00109
– year: 2003
  ident: ref1
  publication-title: Combinatorial Optimization Polyhedra and Efficiency
– ident: ref44
  doi: 10.1109/TEVC.2015.2511142
– ident: ref28
  doi: 10.1016/j.cie.2007.08.003
– volume: 20
  start-page: 711
  year: 2016
  ident: ref6
  article-title: A hybrid evolutionary immune algorithm for multiobjective optimization problems
  publication-title: IEEE Trans Evol Comput
– ident: ref69
  doi: 10.1109/TEVC.2002.802450
– ident: ref57
  doi: 10.1109/TEVC.2003.810752
– ident: ref24
  doi: 10.1155/2012/879614
– ident: ref73
  doi: 10.1109/TEVC.2010.2077298
SSID ssj0000816898
Score 2.4291441
Snippet This paper studies a specific class of multiobjective combinatorial optimization problems (MOCOPs), namely the permutation-based MOCOPs. Many commonly seen...
SourceID proquest
pubmed
crossref
ieee
SourceType Aggregation Database
Index Database
Enrichment Source
Publisher
StartPage 2139
SubjectTerms Combinatorial analysis
Combinatorial optimization
Computer science
Construction
Decomposition
Encoding
Mathematical programming
multiobjective optimization
Multiple objective analysis
Pareto optimization
Particle swarm optimization
particle swarm optimization (PSO)
permutation-based
Permutations
Schedules
set-based
Traveling salesman problem
Urban areas
Weight
Title Set-Based Discrete Particle Swarm Optimization Based on Decomposition for Permutation-Based Multiobjective Combinatorial Optimization Problems
URI https://ieeexplore.ieee.org/document/8003382
https://www.ncbi.nlm.nih.gov/pubmed/28792909
https://www.proquest.com/docview/2174527814
https://www.proquest.com/docview/1927835794
Volume 48
WOSCitedRecordID wos000435342100016&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: PRVIEE
  databaseName: IEEE Electronic Library (IEL)
  customDbUrl:
  eissn: 2168-2275
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0000816898
  issn: 2168-2267
  databaseCode: RIE
  dateStart: 20130101
  isFulltext: true
  titleUrlDefault: https://ieeexplore.ieee.org/
  providerName: IEEE
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1baxQxFD7U4oMv1rZeRmuJ4IOK085mMpPMo20tPtWFVlifhlxOoMXuys6u_gt_syeXHRRU8C2wmWzg3HMuH8BL7FrRGMNL40kFCtOIUjmrSjUh40_xmNbeRLAJeXGhZrNuugVvx14YRIzFZ3gUljGX7xZ2HZ7KjlVAHlOkcO9I2aZerfE9JQJIROhbTouSvAqZk5iTqju-Ov18Euq45BGXnGxaAICjWIF8g1CJ-ItFihArf_c2o9U53_m_-z6A-9m7ZO8SO-zCFs73YGeD3MCyIO_Bbl4N7FWeO_16H35c4qo8Iavm2Nk1aRNyp9k0cxa7_K6Xt-wjKZjb3LnJ0lZanGEoTM_VX4y8YDYlfb9OSf58Ymz0XZibpF8ZXYlC8hDwE___fuw0QdwMD-HT-fur0w9lhmsobS26Vdk6WaNQVmg7wbb1KBpljba2lpwjNrWRE1QNytopS0Gw9xxdaIT1HXfkRtSPYHu-mOMTYFLrytlKCy9rUQlnSDl0mjtvvTcO2wKqDcl6m2eZB0iNL32MaaquDwTvA8H7TPAC3oyffE2DPP61eT9Qc9yYCVnAwYYv-izqQx9iuoaHyWEFvBh_JiENmRc9x8V66MmNDi9spPsKeJz4aTx7w4ZP__yfz-Ae3UylCuED2F4t1_gc7tpvq-theUiSMFOHURJ-AtOvBWg
linkProvider IEEE
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1baxQxFD6UKuiLta2X0aoRfFBx2tlMZpJ5tK2lYl0XukJ9GnI5gYrdlZ1d_Rf-Zk8y2UFBBd8Cm8kGzj3n8gE8w6YWlTE8N55UoDCVyJWzKlcjMv4Uj2ntTQSbkOOxurhoJhvwauiFQcRYfIb7YRlz-W5uV-Gp7EAF5DFFCvdaJQQv-m6t4UUlQkhE8FtOi5z8CpnSmKOiOZgefToMlVxyn0tOVi1AwFG0QN5BqEX8xSZFkJW_-5vR7pxs_d-Nb8Ot5F-y1z1DbMMGznZga43dwJIo78B2WnXseZo8_WIXfpzjMj8ku-bY8SXpE3Ko2STxFjv_rhdX7AOpmKvUu8n6rbQ4xlCanuq_GPnBbEIaf9Wn-dOJsdV3bj73GpbRlSgoDyE_ScDvx056kJvuDnw8eTM9Os0TYENuS9Es89rJEoWyQtsR1rVHUSlrtLWl5ByxKo0coapQlk5ZCoO95-hCK6xvuCNHorwLm7P5DO8Dk1oXzhZaeFmKQjhD6qHR3HnrvXFYZ1CsSdbaNM08gGp8aWNUUzRtIHgbCN4mgmfwcvjkaz_K41-bdwM1h42JkBnsrfmiTcLetSGqq3iYHZbB0-FnEtOQe9EznK-6lhzp8MZG2i-Dez0_DWev2fDBn__zCdw4nb4_a8_ejt89hJt0S9XXC-_B5nKxwkdw3X5bXnaLx1EefgJfcAfH
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=Set-Based+Discrete+Particle+Swarm+Optimization+Based+on+Decomposition+for+Permutation-Based+Multiobjective+Combinatorial+Optimization+Problems&rft.jtitle=IEEE+transactions+on+cybernetics&rft.au=Yu%2C+Xue&rft.au=Chen%2C+Wei-Neng&rft.au=Gu%2C+Tianlong&rft.au=Zhang%2C+Huaxiang&rft.date=2018-07-01&rft.issn=2168-2267&rft.eissn=2168-2275&rft.volume=48&rft.issue=7&rft.spage=2139&rft.epage=2153&rft_id=info:doi/10.1109%2FTCYB.2017.2728120&rft.externalDBID=n%2Fa&rft.externalDocID=10_1109_TCYB_2017_2728120
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2168-2267&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2168-2267&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2168-2267&client=summon