Large‐Scale Multi‐Objective Optimization Algorithms: A Decade Survey

ABSTRACT Large‐scale multi‐objective optimization problems (LSMOPs) are characterised by concurrent optimization of multiple conflicting objectives and no fewer than 100 decision variables. They widely exist in the fields of practical engineering and scientific research. Over the past decade, many l...

Full description

Saved in:

Bibliographic Details
Published in:	Expert systems Vol. 42; no. 12
Main Authors:	Wang, Pengtao, Wu, Xiangjuan, Deng, Hanqing
Format:	Journal Article
Language:	English
Published:	Oxford Blackwell Publishing Ltd 01.12.2025
Subjects:	Algorithms Computer vision decision variable grouping effective offspring generation Evolutionary algorithms learning model LSMOPs non‐grouping dimensionality reduction Optimization Tracking
ISSN:	0266-4720, 1468-0394
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Abstract	ABSTRACT Large‐scale multi‐objective optimization problems (LSMOPs) are characterised by concurrent optimization of multiple conflicting objectives and no fewer than 100 decision variables. They widely exist in the fields of practical engineering and scientific research. Over the past decade, many large‐scale multi‐objective evolutionary algorithms (LSMOEAs) have emerged to address LSMOPs. This paper systematically reviews and comprehensively analyzes the ideas, advantages, disadvantages, and latest developments of these LSMOEAs. Firstly, it introduces the relevant concepts of LSMOEAs. Then classify them into four categories: decision variable grouping‐based LSMOEAs, non‐grouping dimensionality reduction‐based LSMOEAs, effective offspring generation‐based LSMOEAs, and learning models‐based LSMOEAs. It analyzes representative algorithms in each category, elaborating on their core strategies, advantages, and disadvantages. Finally, it explores the applications of LSMOEAs in computer vision, like tackling pixel‐level correlation, high‐resolution feature redundancy, dynamic target tracking, and complex visual modelling. This paper provides readers with a comprehensive and systematic overview of LSMOEAs, serving as a valuable reference for both researchers entering this field and practitioners seeking to select appropriate algorithms for practical problems.
AbstractList	ABSTRACT Large‐scale multi‐objective optimization problems (LSMOPs) are characterised by concurrent optimization of multiple conflicting objectives and no fewer than 100 decision variables. They widely exist in the fields of practical engineering and scientific research. Over the past decade, many large‐scale multi‐objective evolutionary algorithms (LSMOEAs) have emerged to address LSMOPs. This paper systematically reviews and comprehensively analyzes the ideas, advantages, disadvantages, and latest developments of these LSMOEAs. Firstly, it introduces the relevant concepts of LSMOEAs. Then classify them into four categories: decision variable grouping‐based LSMOEAs, non‐grouping dimensionality reduction‐based LSMOEAs, effective offspring generation‐based LSMOEAs, and learning models‐based LSMOEAs. It analyzes representative algorithms in each category, elaborating on their core strategies, advantages, and disadvantages. Finally, it explores the applications of LSMOEAs in computer vision, like tackling pixel‐level correlation, high‐resolution feature redundancy, dynamic target tracking, and complex visual modelling. This paper provides readers with a comprehensive and systematic overview of LSMOEAs, serving as a valuable reference for both researchers entering this field and practitioners seeking to select appropriate algorithms for practical problems. Large‐scale multi‐objective optimization problems (LSMOPs) are characterised by concurrent optimization of multiple conflicting objectives and no fewer than 100 decision variables. They widely exist in the fields of practical engineering and scientific research. Over the past decade, many large‐scale multi‐objective evolutionary algorithms (LSMOEAs) have emerged to address LSMOPs. This paper systematically reviews and comprehensively analyzes the ideas, advantages, disadvantages, and latest developments of these LSMOEAs. Firstly, it introduces the relevant concepts of LSMOEAs. Then classify them into four categories: decision variable grouping‐based LSMOEAs, non‐grouping dimensionality reduction‐based LSMOEAs, effective offspring generation‐based LSMOEAs, and learning models‐based LSMOEAs. It analyzes representative algorithms in each category, elaborating on their core strategies, advantages, and disadvantages. Finally, it explores the applications of LSMOEAs in computer vision, like tackling pixel‐level correlation, high‐resolution feature redundancy, dynamic target tracking, and complex visual modelling. This paper provides readers with a comprehensive and systematic overview of LSMOEAs, serving as a valuable reference for both researchers entering this field and practitioners seeking to select appropriate algorithms for practical problems.
Author	Wang, Pengtao Wu, Xiangjuan Deng, Hanqing
Author_xml	– sequence: 1 givenname: Pengtao surname: Wang fullname: Wang, Pengtao organization: Ningxia University – sequence: 2 givenname: Xiangjuan orcidid: 0000-0001-8723-5299 surname: Wu fullname: Wu, Xiangjuan email: xjwu@nxu.edu.cn organization: Ningxia University – sequence: 3 givenname: Hanqing surname: Deng fullname: Deng, Hanqing organization: Ningxia University
BookMark	eNp9kEFOwzAQRS0EEm1hwwkisUNKsR0nTthVpVCkoi4KEqysqTsprtKk2EkhrDgCZ-QkuJQ1s5jRSG_mf_0uOSyrEgk5Y7TPfF3iu2v7krJYHpAOE0ka0igTh6RDeZKEQnJ6TLrOrSilTMqkQ8YTsEv8_vyaaSgwuG-K2vhtOl-hrs0Wg-mmNmvzAbWpymBQLCtr6pe1uwoGwTVqWGAwa-wW2xNylEPh8PRv9sjjzehhOA4n09u74WASap5wGTKMQHhLDGSsgSa-pTmDKJtDoheRAB1nSKl3yjNAvYCU5xixWNAUUinmUY-c7_9ubPXaoKvVqmps6SVVxCUXMYtj4amLPaVt5ZzFXG2sWYNtFaNql5TaJaV-k_Iw28NvpsD2H1KNnmbP-5sfwGdurw
Cites_doi	10.1016/J.INS.2023.119253 10.1016/J.ASOC.2024.111341 10.1109/TEVC.2021.3118593 10.1109/TEVC.2008.925798 10.1016/J.INS.2020.02.066 10.1109/ICPR.2016.7900296 10.1109/TCYB.2020.2985081 10.1016/J.INS.2025.122116 10.1109/TEVC.2003.810758 10.1007/978-3-642-33275-3_2 10.1109/TEVC.2013.2281543 10.1109/TII.2017.2676000 10.1109/JAS.2024.124341 10.1016/J.ESWA.2023.121563 10.1016/J.SWEVO.2023.101262 10.1109/TEVC.2019.2896002 10.1145/1390156.1390294 10.1016/J.ASOC.2023.111081 10.1023/A:1008202821328 10.1016/J.SWEVO.2024.101622 10.1016/J.ASOC.2023.110925 10.1109/SSCI.2017.8280974 10.1109/TSMC.2020.3003926 10.1109/TEVC.2019.2918140 10.1109/CoDIT58514.2023.10284137 10.1109/TEVC.2015.2455812 10.1109/TEVC.2005.860762 10.1109/JAS.2022.105425 10.1109/CEC.2016.7743831 10.1016/J.ASOC.2015.04.061 10.1007/S12293‐022‐00385‐6 10.1016/J.INS.2022.07.110 10.1109/TEVC.2016.2600642 10.1109/TEVC.2024.3437762 10.1109/TEVC.2018.2881153 10.1016/J.INS.2024.120719 10.1109/TEVC.2021.3063606 10.1109/TEVC.2007.892759 10.1109/TCYB.2020.2979930 10.1016/J.SWEVO.2022.101045 10.1016/J.INS.2024.121347 10.1109/TEVC.2022.3213006 10.1109/TSMC.2018.2861879 10.1016/J.SWEVO.2020.100792 10.1016/J.INS.2023.119221 10.1007/s40747-022-00714-9 10.1109/ICPICS47731.2019.8942442 10.1016/J.SWEVO.2023.101393 10.1109/CEC48606.2020.9185553 10.1109/TEVC.2017.2704782 10.1016/J.INS.2018.10.007 10.1016/J.ASOC.2020.106947 10.1007/S12065‐019‐00250‐5 10.1016/J.INS.2025.121973 10.1109/TEVC.2021.3119933 10.1109/CEC48606.2020.9185846 10.1016/J.INS.2014.03.128 10.1109/TEVC.2013.2262178 10.1109/TEVC.2013.2281535 10.1016/J.SWEVO.2022.101152 10.1145/298151.298382 10.1109/TCYB.2020.3041325 10.1016/J.SWEVO.2024.101763 10.1109/TCYB.2023.3287596 10.1038/s41598-024-64570-y 10.1007/978-3-540-31880-4_20 10.48550/ARXIV.2411.13420 10.1109/TCYB.2016.2600577 10.1007/1-84628-137-7_6 10.1109/TEVC.2025.3529938 10.1016/J.ASOC.2020.106120 10.1109/TEVC.2017.2694221 10.1109/TNNLS.2021.3113158 10.1109/TCE.2024.3372691 10.1016/J.SWEVO.2024.101606 10.1109/CEC48606.2020.9185876 10.1109/TCYB.2019.2906383 10.1162/106365600568202 10.1109/CEC.2013.6557903 10.1016/J.ESWA.2023.122370 10.1080/01431161.2018.1463112 10.1109/ACCESS.2025.3541271 10.1016/J.INS.2021.11.031 10.1016/J.INS.2023.02.062 10.1016/J.SWEVO.2024.101499 10.1016/J.SWEVO.2023.101377 10.48550/ARXIV.2401.15931 10.1109/CoDIT58514.2023.10284401 10.1109/4235.797969 10.1109/TEVC.2022.3155593 10.1109/TEVC.2022.3230070 10.1109/TEVC.2024.3412049 10.1016/J.ASOC.2015.01.039 10.1016/J.INS.2023.02.055
ContentType	Journal Article
Copyright	2025 John Wiley & Sons Ltd. 2025 John Wiley & Sons, Ltd.
Copyright_xml	– notice: 2025 John Wiley & Sons Ltd. – notice: 2025 John Wiley & Sons, Ltd.
DBID	AAYXX CITATION 7SC 7TB 8FD F28 FR3 JQ2 L7M L~C L~D
DOI	10.1111/exsy.70157
DatabaseName	CrossRef Computer and Information Systems Abstracts Mechanical & Transportation Engineering Abstracts Technology Research Database ANTE: Abstracts in New Technology & Engineering Engineering Research Database ProQuest Computer Science Collection Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional
DatabaseTitle	CrossRef Technology Research Database Computer and Information Systems Abstracts – Academic Mechanical & Transportation Engineering 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
DatabaseTitleList	Technology Research Database CrossRef
DeliveryMethod	fulltext_linktorsrc
Discipline	Computer Science
EISSN	1468-0394
EndPage	n/a
ExternalDocumentID	10_1111_exsy_70157 EXSY70157
Genre	reviewArticle
GrantInformation_xml	– fundername: National Natural Science Foundation of China funderid: 62362056 – fundername: Key R&D Program of Ningxia funderid: 2023BSB03016 – fundername: Natural Science Foundation of Ningxia Province funderid: 2023AAC05010
GroupedDBID	-~X .3N .4S .DC .GA .Y3 05W 0R~ 10A 1OB 1OC 29G 31~ 33P 3SF 4.4 50Y 50Z 51W 51X 52M 52N 52O 52P 52S 52T 52U 52W 52X 5GY 5HH 5LA 5VS 66C 6TJ 702 77I 77K 7PT 8-0 8-1 8-3 8-4 8-5 8UM 8VB 930 9M8 A03 AAESR AAEVG AAHQN AAMMB AAMNL AANHP AANLZ AAONW AASGY AAXRX AAYCA AAZKR ABCQN ABCUV ABDBF ABDPE ABEML ABLJU ABPVW ACAHQ ACBWZ ACCZN ACFBH ACGFS ACIWK ACNCT ACPOU ACRPL ACSCC ACUHS ACXBN ACXQS ACYXJ ADBBV ADEOM ADIZJ ADKYN ADMGS ADMHC ADMLS ADNMO ADOZA ADXAS ADZMN AEFGJ AEIGN AEIMD AEMOZ AENEX AEUYR AEYWJ AFBPY AFEBI AFFPM AFGKR AFWVQ AFZJQ AGHNM AGQPQ AGXDD AGYGG AHBTC AHEFC AHQJS AI. AIDQK AIDYY AIQQE AITYG AIURR AJXKR AKVCP ALAGY ALMA_UNASSIGNED_HOLDINGS ALVPJ AMBMR AMYDB ARCSS ASPBG ATUGU AUFTA AVWKF AZBYB AZFZN AZVAB BAFTC BDRZF BFHJK BHBCM BMNLL BMXJE BNHUX BROTX BRXPI BY8 CAG COF CS3 CWDTD D-E D-F DC6 DCZOG DPXWK DR2 DRFUL DRSTM DU5 EAD EAP EBA EBR EBS EBU EDO EJD EMK EST ESX F00 F01 F04 FEDTE FZ0 G-S G.N GODZA H.T H.X HF~ HGLYW HVGLF HZI HZ~ I-F IHE IX1 J0M K1G K48 LATKE LC2 LC3 LEEKS LH4 LITHE LOXES LP6 LP7 LUTES LW6 LYRES MEWTI MK4 MK~ MRFUL MRSTM MSFUL MSSTM MVM MXFUL MXSTM N04 N05 N9A NF~ O66 O9- OIG P2W P2X P4D PALCI PQQKQ Q.N Q11 QB0 QWB R.K RIWAO RJQFR ROL RX1 SAMSI SUPJJ TAE TH9 TN5 TUS UB1 VH1 W8V W99 WBKPD WH7 WIH WIK WLBEL WOHZO WQJ WXSBR WYISQ XG1 ZL0 ZZTAW ~02 ~IA ~WT AAYXX CITATION O8X 7SC 7TB 8FD F28 FR3 JQ2 L7M L~C L~D
ID	FETCH-LOGICAL-c2627-1e3a43941a75ca065ca8f1a39ba6cd34ac59e0047229aecda82fe315408a874b3
IEDL.DBID	DRFUL
ISICitedReferencesCount	0
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001620772900012&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	0266-4720
IngestDate	Sat Nov 29 14:32:21 EST 2025 Thu Nov 27 00:31:02 EST 2025 Tue Nov 18 09:10:28 EST 2025
IsPeerReviewed	true
IsScholarly	true
Issue	12
Language	English
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c2627-1e3a43941a75ca065ca8f1a39ba6cd34ac59e0047229aecda82fe315408a874b3
Notes	Funding This work was supported by National Natural Science Foundation of China (No. 62362056), the Key R&D Program of Ningxia (No. 2023BSB03016), and the Natural Science Foundation of Ningxia Province (No. 2023AAC05010). ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ORCID	0000-0001-8723-5299
PQID	3272451554
PQPubID	32130
PageCount	18
ParticipantIDs	proquest_journals_3272451554 crossref_primary_10_1111_exsy_70157 wiley_primary_10_1111_exsy_70157_EXSY70157
PublicationCentury	2000
PublicationDate	December 2025 2025-12-00 20251201
PublicationDateYYYYMMDD	2025-12-01
PublicationDate_xml	– month: 12 year: 2025 text: December 2025
PublicationDecade	2020
PublicationPlace	Oxford
PublicationPlace_xml	– name: Oxford
PublicationTitle	Expert systems
PublicationYear	2025
Publisher	Blackwell Publishing Ltd
Publisher_xml	– name: Blackwell Publishing Ltd
References	2021; 25 2015; 34 2023; 78 2023; 34 2022; 70 2017; 47 2024; 149 2015; 30 2000; 8 2020; 522 2022; 26 2020; 13 2024 2023; 83 2025; 712 2025; 686 2018; 39 2009; 13 1997; 11 2024; 237 2023; 27 2020; 50 2024; 239 2019; 23 2003; 7 2024; 70 2022; 609 2025; 29 2024; 154 2020; 89 2022; 75 2014; 18 2024; 674 2024; 28 2024; 29 2024; 150 2012 2023; 15 2006; 10 2017; 21 2023; 644 2008 2023; 643 2005 2024; 54 2024; 11 1999; 3 2025; 13 2020; 509 2024; 14 2018; 22 2007; 11 2021; 51 2014; 279 1999 2022; 583 2021; 99 2023 2021 2020 2022; 8 2024; 91 2017; 13 2022; 9 2019 2016; 20 2018 2024; 86 2017 2023; 631 2022; 52 2016 2020; 24 2024; 88 2014 2024; 89 2013 2021; 60 2025; 705 2023; 639 e_1_2_9_75_1 e_1_2_9_98_1 e_1_2_9_52_1 e_1_2_9_79_1 e_1_2_9_94_1 e_1_2_9_10_1 e_1_2_9_56_1 e_1_2_9_90_1 e_1_2_9_71_1 Kukkonen S. (e_1_2_9_40_1) 2005 e_1_2_9_103_1 e_1_2_9_14_1 e_1_2_9_37_1 e_1_2_9_18_1 e_1_2_9_41_1 e_1_2_9_64_1 e_1_2_9_87_1 e_1_2_9_22_1 e_1_2_9_45_1 e_1_2_9_68_1 e_1_2_9_83_1 e_1_2_9_6_1 e_1_2_9_60_1 e_1_2_9_2_1 e_1_2_9_26_1 e_1_2_9_49_1 e_1_2_9_30_1 e_1_2_9_99_1 e_1_2_9_72_1 e_1_2_9_11_1 e_1_2_9_34_1 e_1_2_9_57_1 e_1_2_9_95_1 e_1_2_9_76_1 e_1_2_9_91_1 e_1_2_9_102_1 e_1_2_9_106_1 Liu S. (e_1_2_9_53_1) 2019 e_1_2_9_15_1 e_1_2_9_38_1 e_1_2_9_19_1 e_1_2_9_42_1 e_1_2_9_88_1 e_1_2_9_61_1 e_1_2_9_46_1 e_1_2_9_84_1 Li Y. (e_1_2_9_48_1) 2021 e_1_2_9_23_1 e_1_2_9_80_1 e_1_2_9_5_1 Sander F. (e_1_2_9_67_1) 2018 e_1_2_9_9_1 e_1_2_9_27_1 e_1_2_9_69_1 e_1_2_9_31_1 e_1_2_9_50_1 e_1_2_9_73_1 e_1_2_9_35_1 e_1_2_9_77_1 e_1_2_9_96_1 e_1_2_9_12_1 e_1_2_9_54_1 e_1_2_9_92_1 e_1_2_9_101_1 e_1_2_9_105_1 e_1_2_9_16_1 e_1_2_9_58_1 e_1_2_9_20_1 e_1_2_9_62_1 e_1_2_9_89_1 e_1_2_9_43_1 e_1_2_9_66_1 e_1_2_9_85_1 e_1_2_9_81_1 e_1_2_9_4_1 Goodfellow I. J. (e_1_2_9_24_1) 2014 Yu W. (e_1_2_9_93_1) 2017 e_1_2_9_28_1 e_1_2_9_47_1 e_1_2_9_74_1 e_1_2_9_51_1 e_1_2_9_78_1 e_1_2_9_13_1 e_1_2_9_32_1 e_1_2_9_55_1 e_1_2_9_97_1 e_1_2_9_70_1 Kingma D. P. (e_1_2_9_39_1) 2014 e_1_2_9_100_1 e_1_2_9_104_1 e_1_2_9_17_1 e_1_2_9_36_1 e_1_2_9_59_1 Qian H. (e_1_2_9_65_1) 2017 e_1_2_9_63_1 e_1_2_9_21_1 e_1_2_9_44_1 e_1_2_9_86_1 Chen H. (e_1_2_9_8_1) 2018 e_1_2_9_7_1 e_1_2_9_82_1 e_1_2_9_3_1 Ho J. (e_1_2_9_33_1) 2020 e_1_2_9_25_1 e_1_2_9_29_1
References_xml	– volume: 83 year: 2023 article-title: Offspring Regeneration Driven by Finite Element Mapping for Large‐Scale Evolutionary Multiobjective Optimization publication-title: Swarm and Evolutionary Computation – volume: 24 start-page: 380 issue: 2 year: 2020 end-page: 393 article-title: An Evolutionary Algorithm for Large‐Scale Sparse Multiobjective Optimization Problems publication-title: IEEE Transactions on Evolutionary Computation – volume: 13 start-page: 30976 year: 2025 end-page: 30992 article-title: Learning‐Driven Algorithm With Dual Evolution Patterns for Solving Large‐Scale Multiobjective Optimization Problems publication-title: IEEE Access – volume: 22 start-page: 260 issue: 2 year: 2018 end-page: 275 article-title: A Framework for Large‐Scale Multiobjective Optimization Based on Problem Transformation publication-title: IEEE Transactions on Evolutionary Computation – volume: 522 start-page: 1 year: 2020 end-page: 16 article-title: Enhancing MOEA/D With Information Feedback Models for Large‐Scale Many‐Objective Optimization publication-title: Information Sciences – volume: 643 year: 2023 article-title: An Extended Fuzzy Decision Variables Framework for Solving Large‐Scale Multiobjective Optimization Problems publication-title: Information Sciences – volume: 25 start-page: 724 issue: 4 year: 2021 end-page: 738 article-title: Large‐Scale Evolutionary Multiobjective Optimization Assisted by Directed Sampling publication-title: IEEE Transactions on Evolutionary Computation – start-page: 4220 year: 2016 end-page: 4225 – volume: 70 year: 2022 article-title: Solve Large‐Scale Many‐Objective Optimization Problems Based on Dual Analysis of Objective Space and Decision Space publication-title: Swarm and Evolutionary Computation – start-page: 468 year: 2016 end-page: 475 – volume: 27 start-page: 67 issue: 1 year: 2023 end-page: 81 article-title: Learning to Accelerate Evolutionary Search for Large‐Scale Multiobjective Optimization publication-title: IEEE Transactions on Evolutionary Computation – volume: 237 year: 2024 article-title: A Learning and Potential Area‐Mining Evolutionary Algorithm for Large‐Scale Multi‐Objective Optimization publication-title: Expert Systems With Applications – start-page: 72 year: 2021 end-page: 85 – volume: 18 start-page: 378 issue: 3 year: 2014 end-page: 393 article-title: Cooperative co‐Evolution With Differential Grouping for Large Scale Optimization publication-title: IEEE Transactions on Evolutionary Computation – volume: 89 year: 2024 article-title: An Improved Problem Transformation Algorithm for Large‐Scale Multi‐Objective Optimization publication-title: Swarm Intelligence – start-page: 1 year: 2017 end-page: 8 – volume: 705 year: 2025 article-title: Learning Improvement Representations to Accelerate Evolutionary Large‐Scale Multiobjective Optimization publication-title: Information Sciences – start-page: 1096 year: 2008 end-page: 1103 – volume: 14 issue: 1 year: 2024 article-title: A Multi ‐ Population Multi ‐ Stage Adaptive Weighted Large ‐ Scale Multi ‐ Objective Optimization Algorithm Framework publication-title: Scientific Reports – volume: 279 start-page: 396 year: 2014 end-page: 415 article-title: Numerical Solution of Systems of Second‐Order Boundary Value Problems Using Continuous Genetic Algorithm publication-title: Information Sciences – volume: 154 year: 2024 article-title: Clustering‐Based Genetic Offspring Generation for Solving Multi‐Objective Optimization Problems With Intricate Pareto Sets publication-title: Applied Soft Computing – volume: 13 start-page: 2030 issue: 4 year: 2017 end-page: 2038 article-title: A Distributed Parallel Cooperative Coevolutionary Multiobjective Evolutionary Algorithm for Large‐Scale Optimization publication-title: IEEE Transactions on Industrial Informatics – volume: 18 start-page: 577 issue: 4 year: 2014 end-page: 601 article-title: An Evolutionary Many‐Objective Optimization Algorithm Using Reference‐Point‐Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints publication-title: IEEE Transactions on Evolutionary Computation – volume: 712 year: 2025 article-title: Variational Graph Autoencoder‐Driven Balancing Strategy for Multimodal Multi‐Objective Optimization publication-title: Information Sciences – volume: 29 start-page: 1834 year: 2024 end-page: 1848 article-title: Learning to Evolve With Guiding Solutions Generated by Generative Adversarial Network publication-title: IEEE Transactions on Evolutionary Computation – volume: 9 start-page: 1952 issue: 11 year: 2022 end-page: 1966 article-title: A bi‐Population Cooperative Optimization Algorithm Assisted by an Autoencoder for Medium‐Scale Expensive Problems publication-title: IEEE/CAA Journal of Automatica Sinica – volume: 23 start-page: 525 issue: 3 year: 2019 end-page: 537 article-title: A Scalable Indicator‐Based Evolutionary Algorithm for Large‐Scale Multiobjective Optimization publication-title: IEEE Transactions on Evolutionary Computation – year: 2024 article-title: EmoDM: A Diffusion Model for Evolutionary Multi‐Objective Optimization publication-title: Computing Research Repository – volume: 75 year: 2022 article-title: Offspring Regeneration Method Based on Bi‐Level Sampling for Large‐Scale Evolutionary Multi‐Objective Optimization publication-title: Swarm and Evolutionary Computation – start-page: 2758 year: 2013 end-page: 2765 – start-page: 2014 year: 2014 – volume: 22 start-page: 97 issue: 1 year: 2018 end-page: 112 article-title: A Decision Variable Clustering‐Based Evolutionary Algorithm for Large‐Scale Many‐Objective Optimization publication-title: IEEE Transactions on Evolutionary Computation – start-page: 2672 year: 2014 end-page: 2680 – start-page: 1560 year: 2019 end-page: 1567 – volume: 7 start-page: 117 issue: 2 year: 2003 end-page: 132 article-title: Performance Assessment of Multiobjective Optimizers: An Analysis and Review publication-title: IEEE Transactions on Evolutionary Computation – volume: 23 start-page: 949 issue: 6 year: 2019 end-page: 961 article-title: Accelerating Large‐Scale Multiobjective Optimization via Problem Reformulation publication-title: IEEE Transactions on Evolutionary Computation – start-page: 549 year: 2023 end-page: 554 – volume: 29 start-page: 444 issue: 2 year: 2025 end-page: 458 article-title: Causal Inference‐Based Large‐Scale Multiobjective Optimization publication-title: IEEE Transactions on Evolutionary Computation – volume: 11 start-page: 341 issue: 4 year: 1997 end-page: 359 article-title: Differential Evolution ‐ A Simple and Efficient Heuristic for Global Optimization Over Continuous Spaces publication-title: Journal of Global Optimization – volume: 34 start-page: 286 year: 2015 end-page: 300 article-title: Distributed Evolutionary Algorithms and Their Models: A Survey of the State‐of‐the‐Art publication-title: Applied Soft Computing – volume: 3 start-page: 257 issue: 4 year: 1999 end-page: 271 article-title: Multiobjective Evolutionary Algorithms: A Comparative Case Study and the Strength Pareto Approach publication-title: IEEE Transactions on Evolutionary Computation – volume: 60 year: 2021 article-title: Multiobjective Multiple Features Fusion: A Case Study in Image Segmentation publication-title: Swarm Intelligence – volume: 8 start-page: 173 issue: 2 year: 2000 end-page: 195 article-title: Comparison of Multiobjective Evolutionary Algorithms: Empirical Results publication-title: Evolutionary Computation – start-page: 351 year: 1999 end-page: 357 – volume: 52 start-page: 786 issue: 2 year: 2022 end-page: 798 article-title: Adaptive Offspring Generation for Evolutionary Large‐Scale Multiobjective Optimization publication-title: IEEE Transactions on Systems, Man, and Cybernetics: Systems – start-page: 156 year: 2019 end-page: 159 – volume: 26 start-page: 248 issue: 2 year: 2022 end-page: 262 article-title: A Multivariation Multifactorial Evolutionary Algorithm for Large‐Scale Multiobjective Optimization publication-title: IEEE Transactions on Evolutionary Computation – volume: 631 start-page: 449 year: 2023 end-page: 467 article-title: An Evolutionary Algorithm Based on Dynamic Sparse Grouping for Sparse Large Scale Multiobjective Optimization publication-title: Information Sciences – volume: 51 start-page: 3115 issue: 6 year: 2021 end-page: 3128 article-title: Solving Large‐Scale Multiobjective Optimization Problems With Sparse Optimal Solutions via Unsupervised Neural Networks publication-title: IEEE Transactions on Cybernetics – volume: 583 start-page: 266 year: 2022 end-page: 287 article-title: Multi‐Objective Optimization Based on an Adaptive Competitive Swarm Optimizer publication-title: Information Sciences – volume: 11 start-page: 712 issue: 6 year: 2007 end-page: 731 article-title: MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition publication-title: IEEE Transactions on Evolutionary Computation – start-page: 105 year: 2005 end-page: 145 – volume: 21 start-page: 929 issue: 6 year: 2017 end-page: 942 article-title: DG2: A Faster and More Accurate Differential Grouping for Large‐Scale Black‐Box Optimization publication-title: IEEE Transactions on Evolutionary Computation – volume: 644 year: 2023 article-title: Cooperative Coevolutionary Competition Swarm Optimizer With Perturbation for High‐Dimensional Multi‐Objective Optimization publication-title: Information Sciences – volume: 20 start-page: 275 issue: 2 year: 2016 end-page: 298 article-title: A Multiobjective Evolutionary Algorithm Based on Decision Variable Analyses for Multiobjective Optimization Problems With Large‐Scale Variables publication-title: IEEE Transactions on Evolutionary Computation – volume: 39 start-page: 6572 issue: 20 year: 2018 end-page: 6586 article-title: Enhancing Multispectral Imagery Spatial Resolution Using Optimized Adaptive PCA and High‐Pass Modulation publication-title: International Journal of Remote Sensing – volume: 47 start-page: 4108 issue: 12 year: 2017 end-page: 4121 article-title: Test Problems for Large‐Scale Multiobjective and Many‐Objective Optimization publication-title: IEEE Transactions on Cybernetics – volume: 86 year: 2024 article-title: A Modified Competitive Swarm Optimizer Guided by Space Sampling for Large‐Scale Multi‐Objective Optimization publication-title: Swarm and Evolutionary Computation – volume: 52 start-page: 6784 issue: 7 year: 2022 end-page: 6797 article-title: A Pattern Mining‐Based Evolutionary Algorithm for Large‐Scale Sparse Multiobjective Optimization Problems publication-title: IEEE Transactions on Cybernetics – volume: 27 start-page: 445 issue: 3 year: 2023 end-page: 459 article-title: A Fuzzy Decision Variables Framework for Large‐Scale Multiobjective Optimization publication-title: IEEE Transactions on Evolutionary Computation – volume: 88 year: 2024 article-title: Deep Reinforcement Learning Assisted Automated Guiding Vector Selection for Large‐Scale Sparse Multi‐Objective Optimization publication-title: Swarm Intelligence – volume: 13 start-page: 284 issue: 2 year: 2009 end-page: 302 article-title: Multiobjective Optimization Problems With Complicated Pareto Sets, MOEA/D and NSGA‐II publication-title: IEEE Transactions on Evolutionary Computation – volume: 28 start-page: 32 issue: 1 year: 2024 end-page: 46 article-title: An Efficient Differential Grouping Algorithm for Large‐Scale Global Optimization publication-title: IEEE Transactions on Evolutionary Computation – volume: 89 year: 2020 article-title: A Clustering and Dimensionality Reduction Based Evolutionary Algorithm for Large‐Scale Multi‐Objective Problems publication-title: Applied Soft Computing – volume: 15 start-page: 219 issue: 2 year: 2023 end-page: 235 article-title: Efficient Automatically Evolving Convolutional Neural Network for Image Denoising publication-title: Memetic Computing – volume: 674 year: 2024 article-title: A Two‐Stage Direction‐Guided Evolutionary Algorithm for Large‐Scale Multiobjective Optimization publication-title: Information Sciences – volume: 639 year: 2023 article-title: A Pearson Correlation‐Based Adaptive Variable Grouping Method for Large‐Scale Multi‐Objective Optimization publication-title: Information Sciences – start-page: 1 year: 2020 end-page: 8 – volume: 54 start-page: 3502 issue: 6 year: 2024 end-page: 3515 article-title: Neural Net‐Enhanced Competitive Swarm Optimizer for Large‐Scale Multiobjective Optimization publication-title: IEEE Transactions on Cybernetics – start-page: 14 year: 2012 end-page: 36 – start-page: 875 year: 2017 end-page: 881 – start-page: 2199 year: 2023 end-page: 2204 – volume: 150 year: 2024 article-title: A Problem Transformation‐Based and Decomposition‐Based Evolutionary Algorithm for Large‐Scale Multiobjective Optimization publication-title: Applied Soft Computing – start-page: 223 year: 2018 end-page: 232 – volume: 28 start-page: 47 issue: 1 year: 2024 end-page: 61 article-title: Large‐Scale Multiobjective Optimization via Reformulated Decision Variable Analysis publication-title: IEEE Transactions on Evolutionary Computation – volume: 91 year: 2024 article-title: Learning‐Guided Cross‐Sampling for Large‐Scale Evolutionary Multi‐Objective Optimization publication-title: Swarm and Evolutionary Computation – volume: 149 year: 2024 article-title: Adaptive Multi‐Objective Competitive Swarm Optimization Algorithm Based on Kinematic Analysis for Municipal Solid Waste Incineration publication-title: Applied Soft Computing – volume: 34 start-page: 4631 issue: 8 year: 2023 end-page: 4645 article-title: Manifold Interpolation for Large‐Scale Multiobjective Optimization via Generative Adversarial Networks publication-title: IEEE Transactions on Neural Networks and Learning Systems – volume: 30 start-page: 48 year: 2015 end-page: 57 article-title: A Multiobjective Spatial Fuzzy Clustering Algorithm for Image Segmentation publication-title: Applied Soft Computing – volume: 50 start-page: 4732 issue: 11 year: 2020 end-page: 4745 article-title: A Hybrid Multiobjective Memetic Algorithm for Multiobjective Periodic Vehicle Routing Problem With Time Windows publication-title: IEEE Transactions on Systems, Man, and Cybernetics: Systems – volume: 239 year: 2024 article-title: Directed Quick Search Guided Evolutionary Framework for Large‐Scale Multi‐Objective Optimization Problems publication-title: Expert Systems With Applications – volume: 29 start-page: 1112 year: 2024 end-page: 1126 article-title: Adversarial AutoEncoder‐Based Large‐Scale Dynamic Multi‐Objective Evolutionary Algorithm publication-title: IEEE Transactions on Evolutionary Computation – volume: 78 year: 2023 article-title: Cooperative Coevolutionary Multi‐Guide Particle Swarm Optimization Algorithm for Large‐Scale Multi‐Objective Optimization Problems publication-title: Swarm Intelligence – volume: 13 start-page: 59 issue: 1 year: 2020 end-page: 68 article-title: A Node‐Priority Based Large‐Scale Overlapping Community Detection Using Evolutionary Multi‐Objective Optimization publication-title: Evolutionary Intelligence – volume: 10 start-page: 527 issue: 5 year: 2006 end-page: 549 article-title: A Distributed Cooperative Coevolutionary Algorithm for Multiobjective Optimization publication-title: IEEE Transactions on Evolutionary Computation – volume: 83 year: 2023 article-title: A Population Cooperation Based Particle Swarm Optimization Algorithm for Large‐Scale Multi‐Objective Optimization publication-title: Swarm Intelligence – volume: 8 start-page: 4697 issue: 6 year: 2022 end-page: 4725 article-title: A Competitive Swarm Optimizer With Probabilistic Criteria for Many‐Objective Optimization Problems publication-title: Complex & Intelligent Systems – volume: 50 start-page: 3696 issue: 8 year: 2020 end-page: 3708 article-title: Efficient Large‐Scale Multiobjective Optimization Based on a Competitive Swarm Optimizer publication-title: IEEE Transactions on Cybernetics – start-page: 729 year: 2018 end-page: 736 – volume: 686 year: 2025 article-title: A Two‐Stage Accelerated Search Strategy for Large‐Scale Multi‐Objective Evolutionary Algorithm publication-title: Information Sciences – volume: 11 start-page: 1342 issue: 6 year: 2024 end-page: 1357 article-title: A Two‐Layer Encoding Learning Swarm Optimizer Based on Frequent Itemsets for Sparse Large‐Scale Multi‐Objective Optimization publication-title: IEEE/CAA Journal of Automatica Sinica – year: 2020 – year: 2024 article-title: Heuristically Adaptive Diffusion‐Model Evolutionary Strategy publication-title: Computing Research Repository – volume: 51 start-page: 3129 issue: 6 year: 2021 end-page: 3142 article-title: Evolutionary Multiobjective Optimization Driven by Generative Adversarial Networks (GANs) publication-title: IEEE Transactions on Cybernetics – volume: 509 start-page: 457 year: 2020 end-page: 469 article-title: Solving Large‐Scale Many‐Objective Optimization Problems by Covariance Matrix Adaptation Evolution Strategy With Scalable Small Subpopulations publication-title: Information Sciences – start-page: 280 year: 2005 end-page: 295 – volume: 18 start-page: 348 issue: 3 year: 2014 end-page: 365 article-title: Shift‐Based Density Estimation for Pareto‐Based Algorithms in Many‐Objective Optimization publication-title: IEEE Transactions on Evolutionary Computation – start-page: 443 year: 2005 end-page: 450 – volume: 70 start-page: 3867 issue: 1 year: 2024 end-page: 3874 article-title: Securing VANETs: Multi‐Objective Intrusion Detection With Variational Autoencoders publication-title: IEEE Transactions on Consumer Electronics – start-page: 526 year: 2017 end-page: 530 – volume: 99 year: 2021 article-title: Large‐Scale Many‐Objective Particle Swarm Optimizer With Fast Convergence Based on Alpha‐Stable Mutation and Logistic Function publication-title: Applied Soft Computing – volume: 609 start-page: 1601 year: 2022 end-page: 1620 article-title: A Self‐Exploratory Competitive Swarm Optimization Algorithm for Large‐Scale Multiobjective Optimization publication-title: Information Sciences – ident: e_1_2_9_62_1 doi: 10.1016/J.INS.2023.119253 – ident: e_1_2_9_46_1 doi: 10.1016/J.ASOC.2024.111341 – start-page: 223 volume-title: PEA: Parallel Evolutionary Algorithm by Separating Convergence and Diversity for Large‐Scale Multi‐Objective Optimization year: 2018 ident: e_1_2_9_8_1 – ident: e_1_2_9_92_1 doi: 10.1109/TEVC.2021.3118593 – ident: e_1_2_9_44_1 doi: 10.1109/TEVC.2008.925798 – ident: e_1_2_9_98_1 doi: 10.1016/J.INS.2020.02.066 – ident: e_1_2_9_38_1 doi: 10.1109/ICPR.2016.7900296 – start-page: 875 volume-title: Proceedings of the AAAI Conference on Artificial Intelligence year: 2017 ident: e_1_2_9_65_1 – ident: e_1_2_9_29_1 doi: 10.1109/TCYB.2020.2985081 – ident: e_1_2_9_91_1 doi: 10.1016/J.INS.2025.122116 – start-page: 729 volume-title: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2018, Kyoto, Japan, July 15–19, 2018 year: 2018 ident: e_1_2_9_67_1 – ident: e_1_2_9_104_1 doi: 10.1109/TEVC.2003.810758 – ident: e_1_2_9_20_1 doi: 10.1007/978-3-642-33275-3_2 – ident: e_1_2_9_60_1 doi: 10.1109/TEVC.2013.2281543 – ident: e_1_2_9_5_1 doi: 10.1109/TII.2017.2676000 – ident: e_1_2_9_63_1 doi: 10.1109/JAS.2024.124341 – ident: e_1_2_9_86_1 doi: 10.1016/J.ESWA.2023.121563 – ident: e_1_2_9_58_1 doi: 10.1016/J.SWEVO.2023.101262 – ident: e_1_2_9_30_1 doi: 10.1109/TEVC.2019.2896002 – ident: e_1_2_9_49_1 – ident: e_1_2_9_81_1 doi: 10.1145/1390156.1390294 – ident: e_1_2_9_89_1 doi: 10.1016/J.ASOC.2023.111081 – ident: e_1_2_9_72_1 doi: 10.1023/A:1008202821328 – ident: e_1_2_9_73_1 doi: 10.1016/J.SWEVO.2024.101622 – ident: e_1_2_9_35_1 doi: 10.1016/J.ASOC.2023.110925 – ident: e_1_2_9_101_1 doi: 10.1109/SSCI.2017.8280974 – ident: e_1_2_9_28_1 doi: 10.1109/TSMC.2020.3003926 – ident: e_1_2_9_78_1 doi: 10.1109/TEVC.2019.2918140 – ident: e_1_2_9_12_1 doi: 10.1109/CoDIT58514.2023.10284137 – ident: e_1_2_9_57_1 doi: 10.1109/TEVC.2015.2455812 – ident: e_1_2_9_74_1 doi: 10.1109/TEVC.2005.860762 – ident: e_1_2_9_13_1 doi: 10.1109/JAS.2022.105425 – ident: e_1_2_9_70_1 doi: 10.1109/CEC.2016.7743831 – ident: e_1_2_9_23_1 doi: 10.1016/J.ASOC.2015.04.061 – ident: e_1_2_9_17_1 doi: 10.1007/S12293‐022‐00385‐6 – ident: e_1_2_9_64_1 doi: 10.1016/J.INS.2022.07.110 – ident: e_1_2_9_97_1 doi: 10.1109/TEVC.2016.2600642 – ident: e_1_2_9_22_1 doi: 10.1109/TEVC.2024.3437762 – ident: e_1_2_9_34_1 doi: 10.1109/TEVC.2018.2881153 – ident: e_1_2_9_105_1 doi: 10.1016/J.INS.2024.120719 – ident: e_1_2_9_66_1 doi: 10.1109/TEVC.2021.3063606 – ident: e_1_2_9_96_1 doi: 10.1109/TEVC.2007.892759 – ident: e_1_2_9_77_1 doi: 10.1109/TCYB.2020.2979930 – ident: e_1_2_9_94_1 doi: 10.1016/J.SWEVO.2022.101045 – ident: e_1_2_9_14_1 doi: 10.1016/J.INS.2024.121347 – ident: e_1_2_9_26_1 doi: 10.1109/TEVC.2022.3213006 – ident: e_1_2_9_83_1 doi: 10.1109/TSMC.2018.2861879 – ident: e_1_2_9_50_1 doi: 10.1016/J.SWEVO.2020.100792 – ident: e_1_2_9_84_1 doi: 10.1016/J.INS.2023.119221 – ident: e_1_2_9_31_1 doi: 10.1007/s40747-022-00714-9 – ident: e_1_2_9_9_1 doi: 10.1109/ICPICS47731.2019.8942442 – ident: e_1_2_9_32_1 doi: 10.1016/J.SWEVO.2023.101393 – ident: e_1_2_9_27_1 doi: 10.1109/CEC48606.2020.9185553 – ident: e_1_2_9_100_1 doi: 10.1109/TEVC.2017.2704782 – ident: e_1_2_9_7_1 doi: 10.1016/J.INS.2018.10.007 – ident: e_1_2_9_11_1 doi: 10.1016/J.ASOC.2020.106947 – ident: e_1_2_9_6_1 doi: 10.1007/S12065‐019‐00250‐5 – start-page: 2014 volume-title: 2nd International Conference on Learning Representations year: 2014 ident: e_1_2_9_39_1 – ident: e_1_2_9_54_1 doi: 10.1016/J.INS.2025.121973 – ident: e_1_2_9_19_1 doi: 10.1109/TEVC.2021.3119933 – ident: e_1_2_9_3_1 doi: 10.1109/CEC48606.2020.9185846 – ident: e_1_2_9_4_1 doi: 10.1016/J.INS.2014.03.128 – ident: e_1_2_9_47_1 doi: 10.1109/TEVC.2013.2262178 – start-page: 443 volume-title: GDE3: The Third Evolution Step of Generalized Differential Evolution year: 2005 ident: e_1_2_9_40_1 – ident: e_1_2_9_15_1 doi: 10.1109/TEVC.2013.2281535 – ident: e_1_2_9_55_1 doi: 10.1016/J.SWEVO.2022.101152 – ident: e_1_2_9_80_1 doi: 10.1145/298151.298382 – ident: e_1_2_9_76_1 doi: 10.1109/TCYB.2020.3041325 – ident: e_1_2_9_82_1 doi: 10.1016/J.SWEVO.2024.101763 – ident: e_1_2_9_45_1 doi: 10.1109/TCYB.2023.3287596 – ident: e_1_2_9_88_1 doi: 10.1038/s41598-024-64570-y – ident: e_1_2_9_37_1 doi: 10.1007/978-3-540-31880-4_20 – ident: e_1_2_9_25_1 doi: 10.48550/ARXIV.2411.13420 – ident: e_1_2_9_10_1 doi: 10.1109/TCYB.2016.2600577 – start-page: 1560 volume-title: Automatic Construction of Parallel Portfolios via Explicit Instance Grouping year: 2019 ident: e_1_2_9_53_1 – ident: e_1_2_9_16_1 doi: 10.1007/1-84628-137-7_6 – ident: e_1_2_9_42_1 doi: 10.1109/TEVC.2025.3529938 – ident: e_1_2_9_51_1 doi: 10.1016/J.ASOC.2020.106120 – ident: e_1_2_9_61_1 doi: 10.1109/TEVC.2017.2694221 – start-page: 72 volume-title: Intelligent Computing Theories and Application‐17th International Conference year: 2021 ident: e_1_2_9_48_1 – ident: e_1_2_9_85_1 doi: 10.1109/TNNLS.2021.3113158 – ident: e_1_2_9_59_1 doi: 10.1109/TCE.2024.3372691 – start-page: 2672 volume-title: Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems year: 2014 ident: e_1_2_9_24_1 – ident: e_1_2_9_68_1 doi: 10.1016/J.SWEVO.2024.101606 – ident: e_1_2_9_75_1 doi: 10.1109/CEC48606.2020.9185876 – ident: e_1_2_9_79_1 doi: 10.1109/TCYB.2019.2906383 – ident: e_1_2_9_102_1 doi: 10.1162/106365600568202 – ident: e_1_2_9_2_1 doi: 10.1109/CEC.2013.6557903 – ident: e_1_2_9_87_1 doi: 10.1016/J.ESWA.2023.122370 – ident: e_1_2_9_18_1 doi: 10.1080/01431161.2018.1463112 – ident: e_1_2_9_71_1 doi: 10.1109/ACCESS.2025.3541271 – ident: e_1_2_9_36_1 doi: 10.1016/J.INS.2021.11.031 – ident: e_1_2_9_106_1 doi: 10.1016/J.INS.2023.02.062 – ident: e_1_2_9_21_1 doi: 10.1016/J.SWEVO.2024.101499 – ident: e_1_2_9_56_1 doi: 10.1016/J.SWEVO.2023.101377 – ident: e_1_2_9_90_1 doi: 10.48550/ARXIV.2401.15931 – ident: e_1_2_9_69_1 doi: 10.1109/CoDIT58514.2023.10284401 – volume-title: Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020 year: 2020 ident: e_1_2_9_33_1 – start-page: 526 volume-title: A Mixed Particle Swarm Optimization Algorithm's Application in Image/Video Super‐Resolution Reconstruction year: 2017 ident: e_1_2_9_93_1 – ident: e_1_2_9_103_1 doi: 10.1109/4235.797969 – ident: e_1_2_9_52_1 doi: 10.1109/TEVC.2022.3155593 – ident: e_1_2_9_41_1 doi: 10.1109/TEVC.2022.3230070 – ident: e_1_2_9_43_1 doi: 10.1109/TEVC.2024.3412049 – ident: e_1_2_9_99_1 doi: 10.1016/J.ASOC.2015.01.039 – ident: e_1_2_9_95_1 doi: 10.1016/J.INS.2023.02.055
SSID	ssj0001776
Score	2.3728468
SecondaryResourceType	review_article
Snippet	ABSTRACT Large‐scale multi‐objective optimization problems (LSMOPs) are characterised by concurrent optimization of multiple conflicting objectives and no... Large‐scale multi‐objective optimization problems (LSMOPs) are characterised by concurrent optimization of multiple conflicting objectives and no fewer than...
SourceID	proquest crossref wiley
SourceType	Aggregation Database Index Database Publisher
SubjectTerms	Algorithms Computer vision decision variable grouping effective offspring generation Evolutionary algorithms learning model LSMOPs non‐grouping dimensionality reduction Optimization Tracking
Title	Large‐Scale Multi‐Objective Optimization Algorithms: A Decade Survey
URI	https://onlinelibrary.wiley.com/doi/abs/10.1111%2Fexsy.70157 https://www.proquest.com/docview/3272451554
Volume	42
WOSCitedRecordID	wos001620772900012&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: PRVWIB databaseName: Wiley Online Library Full Collection 2020 customDbUrl: eissn: 1468-0394 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0001776 issn: 0266-4720 databaseCode: DRFUL dateStart: 19970101 isFulltext: true titleUrlDefault: https://onlinelibrary.wiley.com providerName: Wiley-Blackwell
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1LSwMxEB5q68GLb7FaJaAnYWUf2WYjXopt8SBWrEI9LZM06wOtslvF3vwJ_kZ_iUl21-pFEC9LFjYhzM7jS5iZD2A3RBQsTBInUJQ7VDYTB11XP3SwQ89T0hNDSzbBTk-jwYCfVeCwrIXJ-0N8XbgZy7D-2hg4iuybkavXbLLPdDRjM1DzteLSKtTa593Lky9P7DFLLqePGU2HMt8t2pOaTJ7p7J8BaYoyv2NVG2y6C__b5iLMFyCTtHKtWIKKGi3DQkngQAp7XoHjE5MH_vH23td_ShFbjKvfeuIud4Okpx3KQ1GpSVr314_p7fjmITsgLdJWJrOe9J_TFzVZhctu5-Lo2CmoFRzpN33meCpAUxPrIQslahgiMUo8DLjAphwGFGXIVd5JkqOSQ4z8RAUabrkRRoyKYA2qo8eRWgeCknLFXamQJtQTPGJDpueY9VyquKjDTinf-CnvoBGXJw8jnNgKpw6NUvRxYUVZHPjMp4aDhtZhzwr5lxXizqB_ZUcbf_l4E-Z8Q-lrM1QaUB2nz2oLZuXL-DZLtwuN-gTe-9Ky
linkProvider	Wiley-Blackwell
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1bS8MwFD7oJuiL84rTqQF9Eiq9pEvj23AbE-cmboP5VNI01YnbZDfcmz_B3-gvMUm7iy-C-FJSaEL4em4J55wP4NxlLCBuFBmOwNTAPB8ZzDTlQzo7ZlmCW0GoySZIrea12_Q-yc1RtTBxf4j5hZvSDG2vlYKrC-klLRfvw-klke6MrEIaSzlyU5AuPpRb1bkptohml5PnjLyBiW0m_UlVKs9i9k-PtAgzl4NV7W3KmX_ucws2kzATFWK52IYV0duBzIzCASUavQuVqsoE__r4bMh_JZAux5Vv9eAlNoSoLk1KN6nVRIXXp_6gM3ruDq9QARWFyq1HjfFgIqZ70CqXmtcVIyFXMLidt4lhCYepqliLEZczGYhw5kUWc2jA8jx0MOMuFXEvScoED5lnR8KRAZfpMY_gwNmHVK_fEweAGMdUUJMLhiNsBdQjIZFz1HomFjTIwtkMYP8t7qHhz84eChxfg5OF3Ax7P9Gjoe_YxMaKhQZn4UKj_MsKfqndeNSjw798fArrleZd1a_e1G6PYMNWBL86XyUHqdFgLI5hjU9GneHgJBGvb3vn1qI
linkToPdf	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1LS8NAEB58IV6sT6zPBT0JkTw22ay3YlsUSy1WoZ7CZjPRim2lqaI3f4K_0V_i7ia1ehHES0ggu4Qv-83MLjPzARz4QsTMT1PLQ8otKoPUEratLsrZCcdB6cSJEZtgzWbY6fBWkZuja2Hy_hBfB26aGcZea4LjY5J-Yzm-ZK9HTLkzNg2z1OeB4uVs9bJ-3fgyxQ4z6nJqnxFYlLl20Z9Up_JMRv_0SJMw83uwarxNvfTP71yCxSLMJJV8XSzDFPZXoDSWcCAFo1fhtKEzwT_e3tvqXyEx5bjq6SK-zw0huVAmpVfUapLKw-1g2B3d9bJjUiFV1Ln1pP00fMbXNbiu165OTq1CXMGSbuAyy0FP6KpYRzBfChWISBGmjvB4LAKZeFRIn2PeS5ILlIkI3RQ9FXDZoQgZjb11mOkP-rgBREjKkdsSBU2pE_OQJUyN0fPZFHlchv0xwNFj3kMjGu89NDiRAacM22Pso4JHWeS5zKVahYaW4dCg_MsMUa3TvjF3m395eQ_mW9V61Dhrnm_Bgqv1fU26yjbMjIZPuANz8nnUzYa7xer6BEXY1h0
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=Large%E2%80%90Scale+Multi%E2%80%90Objective+Optimization+Algorithms%3A+A+Decade+Survey&rft.jtitle=Expert+systems&rft.au=Wang%2C+Pengtao&rft.au=Wu%2C+Xiangjuan&rft.au=Deng%2C+Hanqing&rft.date=2025-12-01&rft.issn=0266-4720&rft.eissn=1468-0394&rft.volume=42&rft.issue=12&rft_id=info:doi/10.1111%2Fexsy.70157&rft.externalDBID=n%2Fa&rft.externalDocID=10_1111_exsy_70157
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0266-4720&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0266-4720&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0266-4720&client=summon