A double auxiliary optimization constrained multi-objective evolutionary algorithm
In evolutionary constrained multi-objective optimization, the use of auxiliary optimization is gradually attracting attention. It is noted that different forms of auxiliary optimization have different advantages. Combining these advantages in an appropriate manner can further improve the algorithm’s...
Saved in:
| Published in: | Mathematics and computers in simulation Vol. 220; pp. 567 - 579 |
|---|---|
| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier B.V
01.06.2024
|
| Subjects: | |
| ISSN: | 0378-4754, 1872-7166 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Abstract | In evolutionary constrained multi-objective optimization, the use of auxiliary optimization is gradually attracting attention. It is noted that different forms of auxiliary optimization have different advantages. Combining these advantages in an appropriate manner can further improve the algorithm’s performance. Motivated by this inspiration, we propose a double auxiliary optimization constrained multi-objective evolutionary algorithm, namely DAO. In DAO, two auxiliary optimizations, i.e., the unconstrained optimization and the (M+1)-objective optimization, are applied in a proposed tri-population co-evolution strategy. In this strategy, three populations are used to optimize the core optimization and the two auxiliary optimizations in an interactive evolution form. Furthermore, DAO develops a (M+1)-objective environmental selection strategy to deeply explore the boundary between the feasible and infeasible regions. In experimental studies, the performance of DAO and four other state-of-the-art algorithms is evaluated on three distinct benchmark test suites and two intricate real-world problem scenarios. The outcome of the comprehensive evaluation shows the competitive of DAO solving constrained multi-objective optimization problems. |
|---|---|
| AbstractList | In evolutionary constrained multi-objective optimization, the use of auxiliary optimization is gradually attracting attention. It is noted that different forms of auxiliary optimization have different advantages. Combining these advantages in an appropriate manner can further improve the algorithm’s performance. Motivated by this inspiration, we propose a double auxiliary optimization constrained multi-objective evolutionary algorithm, namely DAO. In DAO, two auxiliary optimizations, i.e., the unconstrained optimization and the (M+1)-objective optimization, are applied in a proposed tri-population co-evolution strategy. In this strategy, three populations are used to optimize the core optimization and the two auxiliary optimizations in an interactive evolution form. Furthermore, DAO develops a (M+1)-objective environmental selection strategy to deeply explore the boundary between the feasible and infeasible regions. In experimental studies, the performance of DAO and four other state-of-the-art algorithms is evaluated on three distinct benchmark test suites and two intricate real-world problem scenarios. The outcome of the comprehensive evaluation shows the competitive of DAO solving constrained multi-objective optimization problems. |
| Author | Yan, Bing Yang, Yongkuan Kong, Xiangsong Zhao, Jing |
| Author_xml | – sequence: 1 givenname: Yongkuan orcidid: 0000-0002-8216-4767 surname: Yang fullname: Yang, Yongkuan email: yangyongkuanneu@sina.com – sequence: 2 givenname: Bing surname: Yan fullname: Yan, Bing – sequence: 3 givenname: Xiangsong surname: Kong fullname: Kong, Xiangsong – sequence: 4 givenname: Jing surname: Zhao fullname: Zhao, Jing |
| BookMark | eNqFkE1LxDAQhoOs4Lr6Dzz0D7RO0rRpPQjL4hcsCKLnkKRTTWmbJU0X9dfbup486GnmMM_LvM8pWfSuR0IuKCQUaH7ZJJ0KxnUJA8YTYAlQdkSWtBAsFjTPF2QJqShiLjJ-Qk6HoQGAac-W5GkdVW7ULUZqfLetVf4jcrtgO_upgnV9ZFw_BK9sj1XUjW2wsdMNmmD3GOHeteN8NVOqfXXehrfujBzXqh3w_GeuyMvtzfPmPt4-3j1s1tvYpJCHuNAc05JSpXkORlXClMBZXTDMUDHGeZFhqQSwUpQaGS-xroRSWqdC1xyydEX4Idd4Nwwea7nztptekRTk7EU28uBFzl4kMDl5mbCrX5ix4bvrXLP9D74-wDgV21v0cjAWe4OV9ZMUWTn7d8AX6yeF3Q |
| CitedBy_id | crossref_primary_10_1016_j_autcon_2024_105809 crossref_primary_10_1016_j_eswa_2025_127008 crossref_primary_10_1016_j_matcom_2024_11_009 crossref_primary_10_1016_j_swevo_2025_101937 crossref_primary_10_3390_math13040629 crossref_primary_10_1016_j_engappai_2024_109546 crossref_primary_10_1016_j_swevo_2025_102006 crossref_primary_10_3390_drones8070316 |
| Cites_doi | 10.1016/j.compchemeng.2017.02.017 10.1007/s00521-018-3563-5 10.17352/gje.000070 10.1016/j.ins.2020.02.056 10.3389/fenrg.2023.1293193 10.1016/j.swevo.2021.100940 10.1109/TEVC.2018.2855411 10.1016/j.ins.2021.01.029 10.1109/TSMC.2019.2943973 10.1109/TCYB.2015.2461651 10.1109/4235.996017 10.1109/TCYB.2020.3031642 10.1109/TCYB.2020.3021138 10.1109/TEVC.2020.3004012 10.1109/TEVC.2019.2896967 10.1016/j.asoc.2022.109904 10.1007/s00521-007-0118-6 10.1016/j.asoc.2020.106104 10.1109/TSC.2018.2793266 10.1016/j.ins.2021.07.048 10.1016/j.asoc.2023.110736 10.1007/s00521-012-1046-7 10.1109/MCI.2023.3245719 10.1016/j.asoc.2023.110311 10.1016/j.asoc.2017.06.053 10.1109/TETCI.2023.3236633 10.1109/TEVC.2021.3066301 10.1109/TCYB.2018.2819208 10.1016/j.swevo.2011.03.001 10.1016/j.asoc.2020.107042 10.1162/evco_a_00259 10.1109/TEVC.2019.2894743 10.1016/j.swevo.2020.100651 10.1007/s00521-017-3049-x 10.1016/j.swevo.2018.08.017 10.1016/j.ins.2021.08.038 10.1007/s00521-016-2240-9 10.1016/j.asoc.2019.02.041 10.1016/j.ins.2023.119547 |
| ContentType | Journal Article |
| Copyright | 2024 International Association for Mathematics and Computers in Simulation (IMACS) |
| Copyright_xml | – notice: 2024 International Association for Mathematics and Computers in Simulation (IMACS) |
| DBID | AAYXX CITATION |
| DOI | 10.1016/j.matcom.2024.02.012 |
| DatabaseName | CrossRef |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Computer Science |
| EISSN | 1872-7166 |
| EndPage | 579 |
| ExternalDocumentID | 10_1016_j_matcom_2024_02_012 S0378475424000624 |
| GroupedDBID | --K --M -~X .~1 0R~ 1B1 1RT 1~. 1~5 29M 4.4 457 4G. 5GY 5VS 63O 7-5 71M 8P~ 9JN 9JO AAAKF AAAKG AACTN AAEDT AAEDW AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AAQXK AARIN AAXUO ABAOU ABEFU ABFNM ABJNI ABMAC ABMYL ABUCO ABXDB ABYKQ ACAZW ACDAQ ACGFS ACNNM ACRLP ADBBV ADEZE ADGUI ADMUD ADTZH AEBSH AECPX AEKER AENEX AFFNX AFKWA AFTJW AGHFR AGUBO AGYEJ AHHHB AHJVU AIEXJ AIGVJ AIKHN AITUG AJBFU AJOXV AKRWK ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ APLSM ARUGR AXJTR AZFZN BJAXD BKOJK BLXMC CS3 DU5 EBS EFJIC EFLBG EJD EO8 EO9 EP2 EP3 F5P FDB FEDTE FGOYB FIRID FNPLU FYGXN G-2 G-Q GBLVA HAMUX HLZ HMJ HVGLF HZ~ H~9 IHE J1W JJJVA KOM LG9 M26 M41 MHUIS MO0 N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 R2- RIG RNS ROL RPZ SBC SDF SDG SES SEW SME SPC SPCBC SSB SSD SST SSW SSZ T5K TN5 WUQ XPP ZMT ~02 ~G- 9DU AATTM AAXKI AAYWO AAYXX ABWVN ACLOT ACRPL ACVFH ADCNI ADNMO AEIPS AEUPX AFJKZ AFPUW AGQPQ AIGII AIIUN AKBMS AKYEP ANKPU APXCP CITATION EFKBS ~HD |
| ID | FETCH-LOGICAL-c306t-8b4e3911ab460cad7c9042f82e5ea224485e9a702979be249efd7aabb37bf4053 |
| ISICitedReferencesCount | 9 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001187826400001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 0378-4754 |
| IngestDate | Sat Nov 29 07:17:05 EST 2025 Tue Nov 18 21:19:24 EST 2025 Sat Mar 23 16:41:05 EDT 2024 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Multi-auxiliary optimization Constrained multi-objective optimization Tri-population co-evolution Evolutionary algorithms |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c306t-8b4e3911ab460cad7c9042f82e5ea224485e9a702979be249efd7aabb37bf4053 |
| ORCID | 0000-0002-8216-4767 |
| PageCount | 13 |
| ParticipantIDs | crossref_primary_10_1016_j_matcom_2024_02_012 crossref_citationtrail_10_1016_j_matcom_2024_02_012 elsevier_sciencedirect_doi_10_1016_j_matcom_2024_02_012 |
| PublicationCentury | 2000 |
| PublicationDate | June 2024 2024-06-00 |
| PublicationDateYYYYMMDD | 2024-06-01 |
| PublicationDate_xml | – month: 06 year: 2024 text: June 2024 |
| PublicationDecade | 2020 |
| PublicationTitle | Mathematics and computers in simulation |
| PublicationYear | 2024 |
| Publisher | Elsevier B.V |
| Publisher_xml | – name: Elsevier B.V |
| References | Zhou, Qu, Li, Zhao, Suganthan, Zhang (b47) 2011; 1 Ming, Trivedi, Wang, Srinivasan, Zhang (b27) 2021; 25 Zhu, Lin, Chen (b48) 2018; 30 Ray, Singh, Isaacs, Smith (b32) 2009 Coello, Sierra (b2) 2004 Qiao, Yu, Qu, Liang, Song, Yue, Lin, Tan (b31) 2022 da Silva Maximiano, Vega-Rodríguez, Gómez-Pulido, Sánchez-Pérez (b3) 2013; 22 Deb, Pratap, Agarwal, Meyarivan (b5) 2002; 6 Fan, Li, Cai, Li, Wei, Zhang, Deb, Goodman (b9) 2020; 28 Zitzler, Thiele (b49) 1998 Martinez, Montano, Coello (b25) 2014 Tan, Ma, Mei, Zhang (b33) 2021; 14 Yang, Liu, Tan (b42) 2021; 66 Zhang, Tian, Jiang, Zhang, Jin (b46) 2023; 648 Chen, Lu, Yang (b1) 2008; 17 Fan, Li, Cai, Li, Wei, Zhang, Deb, Goodman (b8) 2019; 44 Tian, Zhang, Su, Zhang, Tan, Jin (b36) 2021; 52 Liu, Qin, Song, Zhang, Li (b20) 2022 Tian, Zhang, Xiao, Zhang, Jin (b37) 2021; 25 Yang, Huang, Kong, Zhao (b39) 2023; 132 Li, Yang, Shang, Li, Ouyang (b19) 2023; 147 Jiao, Zeng, Li, Ong (b13) 2021; 578 Jan, Tairan, Khanum (b12) 2013 Tian, Shi, Zhang, Zhang, Zhang, Zhang (b35) 2023; 11 Datta, Deb, Segev (b4) 2017 Kamboj, Bath, Dhillon (b15) 2017; 28 Fan, Wang, Li, Yuan, You, Yang, Sun, Ruan (b10) 2020; 54 Jiao, Zeng, Li, Yang, Ong (b14) 2021; 51 Yang, Liu, Tan, Wang (b44) 2019; 80 Peng, Liu, Gu (b28) 2017; 60 Ma, Wang (b22) 2019; 23 Demissie, Zhu, Belachew (b6) 2017; 100 Li, Chen, Fu, Yao (b18) 2019; 23 Karami, Dariane (b16) 2022; 7 Yang, Liu, Tan (b41) 2021; 101 Tawhid, Savsani (b34) 2019; 31 Ma, Wang, Song (b23) 2021; 51 Wang, Liang, Zhang (b38) 2019; 49 Zeng, Jiao, Li, Li, Alkasassbeh (b45) 2017; 47 Qiao, Liang, Yu, Wang, Qu, Yue, Guo (b30) 2023; 7 Ming, Gong, Gao (b26) 2023; 18 Ma, Wei, Tian, Cheng, Zhang (b24) 2021; 560 Kong, Yang, Lv, Zhao, Fu (b17) 2023; 141 Qian, Ye, Jiang, Wang (b29) 2016; 46 Yang, Liu, Tan, Liu (b43) 2021; 579 Isaacs, Ray, Smith (b11) 2008 Liu, Wang (b21) 2019; 23 Yang, Liu, Tan (b40) 2020; 89 Dong, Wang, Tang (b7) 2020; 521 Fan (10.1016/j.matcom.2024.02.012_b9) 2020; 28 Liu (10.1016/j.matcom.2024.02.012_b21) 2019; 23 Jiao (10.1016/j.matcom.2024.02.012_b14) 2021; 51 Tian (10.1016/j.matcom.2024.02.012_b36) 2021; 52 Yang (10.1016/j.matcom.2024.02.012_b40) 2020; 89 Chen (10.1016/j.matcom.2024.02.012_b1) 2008; 17 Ma (10.1016/j.matcom.2024.02.012_b23) 2021; 51 Zhang (10.1016/j.matcom.2024.02.012_b46) 2023; 648 Fan (10.1016/j.matcom.2024.02.012_b8) 2019; 44 Ma (10.1016/j.matcom.2024.02.012_b22) 2019; 23 Ray (10.1016/j.matcom.2024.02.012_b32) 2009 Zitzler (10.1016/j.matcom.2024.02.012_b49) 1998 Yang (10.1016/j.matcom.2024.02.012_b43) 2021; 579 Tan (10.1016/j.matcom.2024.02.012_b33) 2021; 14 Tawhid (10.1016/j.matcom.2024.02.012_b34) 2019; 31 Zhou (10.1016/j.matcom.2024.02.012_b47) 2011; 1 Yang (10.1016/j.matcom.2024.02.012_b42) 2021; 66 Deb (10.1016/j.matcom.2024.02.012_b5) 2002; 6 Tian (10.1016/j.matcom.2024.02.012_b37) 2021; 25 Peng (10.1016/j.matcom.2024.02.012_b28) 2017; 60 Liu (10.1016/j.matcom.2024.02.012_b20) 2022 Tian (10.1016/j.matcom.2024.02.012_b35) 2023; 11 Kamboj (10.1016/j.matcom.2024.02.012_b15) 2017; 28 Yang (10.1016/j.matcom.2024.02.012_b44) 2019; 80 Kong (10.1016/j.matcom.2024.02.012_b17) 2023; 141 Datta (10.1016/j.matcom.2024.02.012_b4) 2017 Jan (10.1016/j.matcom.2024.02.012_b12) 2013 Demissie (10.1016/j.matcom.2024.02.012_b6) 2017; 100 Jiao (10.1016/j.matcom.2024.02.012_b13) 2021; 578 Zeng (10.1016/j.matcom.2024.02.012_b45) 2017; 47 Isaacs (10.1016/j.matcom.2024.02.012_b11) 2008 Wang (10.1016/j.matcom.2024.02.012_b38) 2019; 49 Coello (10.1016/j.matcom.2024.02.012_b2) 2004 Zhu (10.1016/j.matcom.2024.02.012_b48) 2018; 30 Yang (10.1016/j.matcom.2024.02.012_b39) 2023; 132 Ma (10.1016/j.matcom.2024.02.012_b24) 2021; 560 Li (10.1016/j.matcom.2024.02.012_b18) 2019; 23 Li (10.1016/j.matcom.2024.02.012_b19) 2023; 147 Ming (10.1016/j.matcom.2024.02.012_b27) 2021; 25 Qiao (10.1016/j.matcom.2024.02.012_b30) 2023; 7 Yang (10.1016/j.matcom.2024.02.012_b41) 2021; 101 Martinez (10.1016/j.matcom.2024.02.012_b25) 2014 Qiao (10.1016/j.matcom.2024.02.012_b31) 2022 Qian (10.1016/j.matcom.2024.02.012_b29) 2016; 46 da Silva Maximiano (10.1016/j.matcom.2024.02.012_b3) 2013; 22 Fan (10.1016/j.matcom.2024.02.012_b10) 2020; 54 Dong (10.1016/j.matcom.2024.02.012_b7) 2020; 521 Ming (10.1016/j.matcom.2024.02.012_b26) 2023; 18 Karami (10.1016/j.matcom.2024.02.012_b16) 2022; 7 |
| References_xml | – volume: 578 start-page: 592 year: 2021 end-page: 614 ident: b13 article-title: Two-type weight adjustments in MOEA/D for highly constrained many-objective optimization publication-title: Inform. Sci. – volume: 25 start-page: 102 year: 2021 end-page: 116 ident: b37 article-title: A coevolutionary framework for constrained multiobjective optimization problems publication-title: IEEE Trans. Evol. Comput. – start-page: 1 year: 2022 ident: b20 article-title: Multiobjective-based constraint-handling technique for evolutionary constrained multiobjective optimization: A new perspective publication-title: IEEE Trans. Evol. Comput. – volume: 25 start-page: 739 year: 2021 end-page: 753 ident: b27 article-title: A dual-population-based evolutionary algorithm for constrained multiobjective optimization publication-title: IEEE Trans. Evol. Comput. – volume: 11 year: 2023 ident: b35 article-title: Solving optimal power flow problems via a constrained many-objective co-evolutionary algorithm publication-title: Front. Energy Res. – volume: 14 start-page: 458 year: 2021 end-page: 471 ident: b33 article-title: Evolutionary multi-objective optimization for web service location allocation problem publication-title: IEEE Trans. Serv. Comput. – volume: 521 start-page: 209 year: 2020 end-page: 230 ident: b7 article-title: MOEA/D with a self-adaptive weight vector adjustment strategy based on chain segmentation publication-title: Inform. Sci. – volume: 28 start-page: 339 year: 2020 end-page: 378 ident: b9 article-title: Difficulty adjustable and scalable constrained multiobjective test problem toolkit publication-title: Evol. Comput. – start-page: 49 year: 2013 end-page: 54 ident: b12 article-title: Threshold based dynamic and adaptive penalty functions for constrained multiobjective optimization publication-title: International Conference on Artificial Intelligence, Modelling and Simulation – volume: 560 start-page: 68 year: 2021 end-page: 91 ident: b24 article-title: A multi-stage evolutionary algorithm for multi-objective optimization with complex constraints publication-title: Inform. Sci. – volume: 52 start-page: 9559 year: 2021 end-page: 9572 ident: b36 article-title: Balancing objective optimization and constraint satisfaction in constrained evolutionary multiobjective optimization publication-title: IEEE Trans. Cybern. – volume: 648 year: 2023 ident: b46 article-title: Design and analysis of helper-problem-assisted evolutionary algorithm for constrained multiobjective optimization publication-title: Inform. Sci. – start-page: 145 year: 2009 end-page: 165 ident: b32 article-title: Infeasibility driven evolutionary algorithm for constrained optimization publication-title: Constraint-Handling in Evolutionary Optimization – volume: 66 year: 2021 ident: b42 article-title: A partition-based constrained multi-objective evolutionary algorithm publication-title: Swarm Evol. Comput. – volume: 30 start-page: 759 year: 2018 end-page: 773 ident: b48 article-title: A gene-level hybrid search framework for multiobjective evolutionary optimization publication-title: Neural Comput. Appl. – volume: 23 start-page: 870 year: 2019 end-page: 884 ident: b21 article-title: Handling constrained multiobjective optimization problems with constraints in both the decision and objective spaces publication-title: IEEE Trans. Evol. Comput. – start-page: 688 year: 2004 end-page: 697 ident: b2 article-title: A study of the parallelization of a coevolutionary multi-objective evolutionary algorithm publication-title: Mexican International Conference on Artificial Intelligence – volume: 17 start-page: 101 year: 2008 end-page: 109 ident: b1 article-title: Multiobjective optimization using population-based extremal optimization publication-title: Neural Comput. Appl. – volume: 44 start-page: 665 year: 2019 end-page: 679 ident: b8 article-title: Push and pull search for solving constrained multi-objective optimization problems publication-title: Swarm Evol. Comput. – volume: 18 start-page: 18 year: 2023 end-page: 30 ident: b26 article-title: Adaptive auxiliary task selection for multitasking-assisted constrained multi-objective optimization [feature] publication-title: IEEE Comput. Intell. Mag. – volume: 6 start-page: 182 year: 2002 end-page: 197 ident: b5 article-title: A fast and elitist multiobjective genetic algorithm: NSGA-II publication-title: IEEE Trans. Evol. Comput. – volume: 100 start-page: 94 year: 2017 end-page: 103 ident: b6 article-title: A multi-objective optimization model for gas pipeline operations publication-title: Comput. Chem. Eng. – volume: 7 start-page: 1098 year: 2023 end-page: 1112 ident: b30 article-title: A self-adaptive evolutionary multi-task based constrained multi-objective evolutionary algorithm publication-title: IEEE Trans. Emerg. Top. Comput. Intell. – volume: 89 year: 2020 ident: b40 article-title: A constrained multi-objective evolutionary algorithm based on decomposition and dynamic constraint-handling mechanism publication-title: Appl. Soft Comput. – volume: 47 start-page: 2678 year: 2017 end-page: 2688 ident: b45 article-title: A general framework of dynamic constrained multiobjective evolutionary algorithms for constrained optimization publication-title: IEEE Trans. Cybern. – volume: 147 year: 2023 ident: b19 article-title: Kriging-assisted indicator-based evolutionary algorithm for expensive multi-objective optimization publication-title: Appl. Soft Comput. – start-page: 2780 year: 2008 end-page: 2787 ident: b11 article-title: Blessings of maintaining infeasible solutions for constrained multi-objective optimization problems publication-title: 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence) – volume: 60 start-page: 613 year: 2017 end-page: 622 ident: b28 article-title: An evolutionary algorithm with directed weights for constrained multi-objective optimization publication-title: Appl. Soft Comput. – volume: 1 start-page: 32 year: 2011 end-page: 49 ident: b47 article-title: Multiobjective evolutionary algorithms: A survey of the state of the art publication-title: Swarm Evol. Comput. – volume: 23 start-page: 303 year: 2019 end-page: 315 ident: b18 article-title: Two-archive evolutionary algorithm for constrained multiobjective optimization publication-title: IEEE Trans. Evol. Comput. – volume: 51 start-page: 5005 year: 2021 end-page: 5016 ident: b23 article-title: A new fitness function with two rankings for evolutionary constrained multiobjective optimization publication-title: IEEE Trans. Syst., Man, Cybern.: Syst. – volume: 132 year: 2023 ident: b39 article-title: A constrained multi-objective evolutionary algorithm assisted by an additional objective function publication-title: Appl. Soft Comput. – start-page: 292 year: 1998 end-page: 301 ident: b49 article-title: Multiobjective optimization using evolutionary algorithms—A comparative case study publication-title: International Conference on Parallel Problem Solving from Nature – volume: 46 start-page: 2056 year: 2016 end-page: 2069 ident: b29 article-title: Constrained multiobjective optimization algorithm based on immune system model publication-title: IEEE Trans. Cybern. – volume: 80 start-page: 42 year: 2019 end-page: 56 ident: b44 article-title: A multi-objective differential evolutionary algorithm for constrained multi-objective optimization problems with low feasible ratio publication-title: Appl. Soft Comput. – volume: 51 start-page: 4834 year: 2021 end-page: 4847 ident: b14 article-title: Handling constrained many-objective optimization problems via problem transformation publication-title: IEEE Trans. Cybern. – volume: 54 year: 2020 ident: b10 article-title: Push and pull search embedded in an M2M framework for solving constrained multi-objective optimization problems publication-title: Swarm Evol. Comput. – volume: 22 start-page: 1447 year: 2013 end-page: 1459 ident: b3 article-title: A new multiobjective artificial bee colony algorithm to solve a real-world frequency assignment problem publication-title: Neural Comput. Appl. – volume: 141 year: 2023 ident: b17 article-title: A dynamic dual-population co-evolution multi-objective evolutionary algorithm for constrained multi-objective optimization problems publication-title: Appl. Soft Comput. – volume: 7 start-page: 104 year: 2022 end-page: 119 ident: b16 article-title: A review and evaluation of multi and many-objective optimization: Methods and algorithms publication-title: Glob. J. Ecol. – start-page: 317 year: 2017 end-page: 324 ident: b4 article-title: A bi-objective hybrid constrained optimization (HyCon) method using a multi-objective and penalty function approach publication-title: 2017 IEEE Congress on Evolutionary Computation – volume: 49 start-page: 2060 year: 2019 end-page: 2072 ident: b38 article-title: Cooperative differential evolution framework for constrained multiobjective optimization publication-title: IEEE Trans. Cybern. – volume: 31 start-page: 915 year: 2019 end-page: 929 ident: b34 article-title: Multi-objective sine-cosine algorithm (MO-SCA) for multi-objective engineering design problems publication-title: Neural Comput. Appl. – volume: 28 start-page: 3521 year: 2017 end-page: 3536 ident: b15 article-title: Multiobjective multiarea unit commitment using hybrid differential evolution algorithm considering import/export and tie-line constraints publication-title: Neural Comput. Appl. – volume: 579 start-page: 796 year: 2021 end-page: 813 ident: b43 article-title: A multi-objective differential evolution algorithm based on domination and constraint-handling switching publication-title: Inform. Sci. – volume: 23 start-page: 972 year: 2019 end-page: 986 ident: b22 article-title: Evolutionary constrained multiobjective optimization: Test suite construction and performance comparisons publication-title: IEEE Trans. Evol. Comput. – year: 2022 ident: b31 article-title: Dynamic auxiliary task-based evolutionary multitasking for constrained multi-objective optimization publication-title: IEEE Trans. Evol. Comput. – volume: 101 year: 2021 ident: b41 article-title: A multi-objective evolutionary algorithm for steady-state constrained multi-objective optimization problems publication-title: Appl. Soft Comput. – start-page: 81 year: 2014 end-page: 88 ident: b25 article-title: Constrained Multi-Objective Aerodynamic Shape Optimization Via Swarm Intelligence – volume: 100 start-page: 94 year: 2017 ident: 10.1016/j.matcom.2024.02.012_b6 article-title: A multi-objective optimization model for gas pipeline operations publication-title: Comput. Chem. Eng. doi: 10.1016/j.compchemeng.2017.02.017 – volume: 30 start-page: 759 issue: 3 year: 2018 ident: 10.1016/j.matcom.2024.02.012_b48 article-title: A gene-level hybrid search framework for multiobjective evolutionary optimization publication-title: Neural Comput. Appl. doi: 10.1007/s00521-018-3563-5 – volume: 7 start-page: 104 issue: 2 year: 2022 ident: 10.1016/j.matcom.2024.02.012_b16 article-title: A review and evaluation of multi and many-objective optimization: Methods and algorithms publication-title: Glob. J. Ecol. doi: 10.17352/gje.000070 – volume: 521 start-page: 209 year: 2020 ident: 10.1016/j.matcom.2024.02.012_b7 article-title: MOEA/D with a self-adaptive weight vector adjustment strategy based on chain segmentation publication-title: Inform. Sci. doi: 10.1016/j.ins.2020.02.056 – volume: 11 year: 2023 ident: 10.1016/j.matcom.2024.02.012_b35 article-title: Solving optimal power flow problems via a constrained many-objective co-evolutionary algorithm publication-title: Front. Energy Res. doi: 10.3389/fenrg.2023.1293193 – volume: 66 year: 2021 ident: 10.1016/j.matcom.2024.02.012_b42 article-title: A partition-based constrained multi-objective evolutionary algorithm publication-title: Swarm Evol. Comput. doi: 10.1016/j.swevo.2021.100940 – volume: 23 start-page: 303 issue: 2 year: 2019 ident: 10.1016/j.matcom.2024.02.012_b18 article-title: Two-archive evolutionary algorithm for constrained multiobjective optimization publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2018.2855411 – volume: 560 start-page: 68 year: 2021 ident: 10.1016/j.matcom.2024.02.012_b24 article-title: A multi-stage evolutionary algorithm for multi-objective optimization with complex constraints publication-title: Inform. Sci. doi: 10.1016/j.ins.2021.01.029 – start-page: 2780 year: 2008 ident: 10.1016/j.matcom.2024.02.012_b11 article-title: Blessings of maintaining infeasible solutions for constrained multi-objective optimization problems – volume: 51 start-page: 5005 issue: 8 year: 2021 ident: 10.1016/j.matcom.2024.02.012_b23 article-title: A new fitness function with two rankings for evolutionary constrained multiobjective optimization publication-title: IEEE Trans. Syst., Man, Cybern.: Syst. doi: 10.1109/TSMC.2019.2943973 – start-page: 1 year: 2022 ident: 10.1016/j.matcom.2024.02.012_b20 article-title: Multiobjective-based constraint-handling technique for evolutionary constrained multiobjective optimization: A new perspective publication-title: IEEE Trans. Evol. Comput. – volume: 46 start-page: 2056 issue: 9 year: 2016 ident: 10.1016/j.matcom.2024.02.012_b29 article-title: Constrained multiobjective optimization algorithm based on immune system model publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2015.2461651 – volume: 6 start-page: 182 issue: 2 year: 2002 ident: 10.1016/j.matcom.2024.02.012_b5 article-title: A fast and elitist multiobjective genetic algorithm: NSGA-II publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/4235.996017 – start-page: 317 year: 2017 ident: 10.1016/j.matcom.2024.02.012_b4 article-title: A bi-objective hybrid constrained optimization (HyCon) method using a multi-objective and penalty function approach – volume: 51 start-page: 4834 issue: 10 year: 2021 ident: 10.1016/j.matcom.2024.02.012_b14 article-title: Handling constrained many-objective optimization problems via problem transformation publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2020.3031642 – volume: 52 start-page: 9559 issue: 9 year: 2021 ident: 10.1016/j.matcom.2024.02.012_b36 article-title: Balancing objective optimization and constraint satisfaction in constrained evolutionary multiobjective optimization publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2020.3021138 – start-page: 145 year: 2009 ident: 10.1016/j.matcom.2024.02.012_b32 article-title: Infeasibility driven evolutionary algorithm for constrained optimization – start-page: 688 year: 2004 ident: 10.1016/j.matcom.2024.02.012_b2 article-title: A study of the parallelization of a coevolutionary multi-objective evolutionary algorithm – volume: 25 start-page: 102 issue: 1 year: 2021 ident: 10.1016/j.matcom.2024.02.012_b37 article-title: A coevolutionary framework for constrained multiobjective optimization problems publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2020.3004012 – volume: 23 start-page: 972 issue: 6 year: 2019 ident: 10.1016/j.matcom.2024.02.012_b22 article-title: Evolutionary constrained multiobjective optimization: Test suite construction and performance comparisons publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2019.2896967 – volume: 132 year: 2023 ident: 10.1016/j.matcom.2024.02.012_b39 article-title: A constrained multi-objective evolutionary algorithm assisted by an additional objective function publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2022.109904 – start-page: 292 year: 1998 ident: 10.1016/j.matcom.2024.02.012_b49 article-title: Multiobjective optimization using evolutionary algorithms—A comparative case study – volume: 17 start-page: 101 issue: 2 year: 2008 ident: 10.1016/j.matcom.2024.02.012_b1 article-title: Multiobjective optimization using population-based extremal optimization publication-title: Neural Comput. Appl. doi: 10.1007/s00521-007-0118-6 – volume: 89 year: 2020 ident: 10.1016/j.matcom.2024.02.012_b40 article-title: A constrained multi-objective evolutionary algorithm based on decomposition and dynamic constraint-handling mechanism publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2020.106104 – start-page: 49 year: 2013 ident: 10.1016/j.matcom.2024.02.012_b12 article-title: Threshold based dynamic and adaptive penalty functions for constrained multiobjective optimization – volume: 14 start-page: 458 issue: 2 year: 2021 ident: 10.1016/j.matcom.2024.02.012_b33 article-title: Evolutionary multi-objective optimization for web service location allocation problem publication-title: IEEE Trans. Serv. Comput. doi: 10.1109/TSC.2018.2793266 – year: 2022 ident: 10.1016/j.matcom.2024.02.012_b31 article-title: Dynamic auxiliary task-based evolutionary multitasking for constrained multi-objective optimization publication-title: IEEE Trans. Evol. Comput. – volume: 578 start-page: 592 year: 2021 ident: 10.1016/j.matcom.2024.02.012_b13 article-title: Two-type weight adjustments in MOEA/D for highly constrained many-objective optimization publication-title: Inform. Sci. doi: 10.1016/j.ins.2021.07.048 – volume: 147 year: 2023 ident: 10.1016/j.matcom.2024.02.012_b19 article-title: Kriging-assisted indicator-based evolutionary algorithm for expensive multi-objective optimization publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2023.110736 – volume: 22 start-page: 1447 issue: 7 year: 2013 ident: 10.1016/j.matcom.2024.02.012_b3 article-title: A new multiobjective artificial bee colony algorithm to solve a real-world frequency assignment problem publication-title: Neural Comput. Appl. doi: 10.1007/s00521-012-1046-7 – volume: 18 start-page: 18 issue: 2 year: 2023 ident: 10.1016/j.matcom.2024.02.012_b26 article-title: Adaptive auxiliary task selection for multitasking-assisted constrained multi-objective optimization [feature] publication-title: IEEE Comput. Intell. Mag. doi: 10.1109/MCI.2023.3245719 – volume: 141 year: 2023 ident: 10.1016/j.matcom.2024.02.012_b17 article-title: A dynamic dual-population co-evolution multi-objective evolutionary algorithm for constrained multi-objective optimization problems publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2023.110311 – volume: 60 start-page: 613 year: 2017 ident: 10.1016/j.matcom.2024.02.012_b28 article-title: An evolutionary algorithm with directed weights for constrained multi-objective optimization publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2017.06.053 – volume: 7 start-page: 1098 issue: 4 year: 2023 ident: 10.1016/j.matcom.2024.02.012_b30 article-title: A self-adaptive evolutionary multi-task based constrained multi-objective evolutionary algorithm publication-title: IEEE Trans. Emerg. Top. Comput. Intell. doi: 10.1109/TETCI.2023.3236633 – volume: 25 start-page: 739 issue: 4 year: 2021 ident: 10.1016/j.matcom.2024.02.012_b27 article-title: A dual-population-based evolutionary algorithm for constrained multiobjective optimization publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2021.3066301 – volume: 49 start-page: 2060 issue: 6 year: 2019 ident: 10.1016/j.matcom.2024.02.012_b38 article-title: Cooperative differential evolution framework for constrained multiobjective optimization publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2018.2819208 – volume: 1 start-page: 32 issue: 1 year: 2011 ident: 10.1016/j.matcom.2024.02.012_b47 article-title: Multiobjective evolutionary algorithms: A survey of the state of the art publication-title: Swarm Evol. Comput. doi: 10.1016/j.swevo.2011.03.001 – volume: 47 start-page: 2678 issue: 9 year: 2017 ident: 10.1016/j.matcom.2024.02.012_b45 article-title: A general framework of dynamic constrained multiobjective evolutionary algorithms for constrained optimization publication-title: IEEE Trans. Cybern. – volume: 101 year: 2021 ident: 10.1016/j.matcom.2024.02.012_b41 article-title: A multi-objective evolutionary algorithm for steady-state constrained multi-objective optimization problems publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2020.107042 – volume: 28 start-page: 339 issue: 3 year: 2020 ident: 10.1016/j.matcom.2024.02.012_b9 article-title: Difficulty adjustable and scalable constrained multiobjective test problem toolkit publication-title: Evol. Comput. doi: 10.1162/evco_a_00259 – volume: 23 start-page: 870 issue: 5 year: 2019 ident: 10.1016/j.matcom.2024.02.012_b21 article-title: Handling constrained multiobjective optimization problems with constraints in both the decision and objective spaces publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2019.2894743 – volume: 54 year: 2020 ident: 10.1016/j.matcom.2024.02.012_b10 article-title: Push and pull search embedded in an M2M framework for solving constrained multi-objective optimization problems publication-title: Swarm Evol. Comput. doi: 10.1016/j.swevo.2020.100651 – volume: 31 start-page: 915 issue: 2 year: 2019 ident: 10.1016/j.matcom.2024.02.012_b34 article-title: Multi-objective sine-cosine algorithm (MO-SCA) for multi-objective engineering design problems publication-title: Neural Comput. Appl. doi: 10.1007/s00521-017-3049-x – volume: 44 start-page: 665 year: 2019 ident: 10.1016/j.matcom.2024.02.012_b8 article-title: Push and pull search for solving constrained multi-objective optimization problems publication-title: Swarm Evol. Comput. doi: 10.1016/j.swevo.2018.08.017 – volume: 579 start-page: 796 year: 2021 ident: 10.1016/j.matcom.2024.02.012_b43 article-title: A multi-objective differential evolution algorithm based on domination and constraint-handling switching publication-title: Inform. Sci. doi: 10.1016/j.ins.2021.08.038 – volume: 28 start-page: 3521 issue: 11 year: 2017 ident: 10.1016/j.matcom.2024.02.012_b15 article-title: Multiobjective multiarea unit commitment using hybrid differential evolution algorithm considering import/export and tie-line constraints publication-title: Neural Comput. Appl. doi: 10.1007/s00521-016-2240-9 – volume: 80 start-page: 42 year: 2019 ident: 10.1016/j.matcom.2024.02.012_b44 article-title: A multi-objective differential evolutionary algorithm for constrained multi-objective optimization problems with low feasible ratio publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2019.02.041 – start-page: 81 year: 2014 ident: 10.1016/j.matcom.2024.02.012_b25 – volume: 648 year: 2023 ident: 10.1016/j.matcom.2024.02.012_b46 article-title: Design and analysis of helper-problem-assisted evolutionary algorithm for constrained multiobjective optimization publication-title: Inform. Sci. doi: 10.1016/j.ins.2023.119547 |
| SSID | ssj0007545 |
| Score | 2.4255638 |
| Snippet | In evolutionary constrained multi-objective optimization, the use of auxiliary optimization is gradually attracting attention. It is noted that different forms... |
| SourceID | crossref elsevier |
| SourceType | Enrichment Source Index Database Publisher |
| StartPage | 567 |
| SubjectTerms | Constrained multi-objective optimization Evolutionary algorithms Multi-auxiliary optimization Tri-population co-evolution |
| Title | A double auxiliary optimization constrained multi-objective evolutionary algorithm |
| URI | https://dx.doi.org/10.1016/j.matcom.2024.02.012 |
| Volume | 220 |
| WOSCitedRecordID | wos001187826400001&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: PRVESC databaseName: Elsevier SD Freedom Collection Journals 2021 customDbUrl: eissn: 1872-7166 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0007545 issn: 0378-4754 databaseCode: AIEXJ dateStart: 19950501 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3db9MwELfKxgMvwPgQAzb5gbfJU-Y4dfxYoSGGtAnBkAovkZ04XUqbTP1S_4v9yzt_ZRlFGyDxElWp3bp3v9yd3d_dIfSurxKay0IQzeOSMKYoEXGhiIgkE9TE2EfKNpvgZ2fpcCg-93pXIRdmNeF1na7X4vK_qhrugbJN6uxfqLv9ULgBr0HpcAW1w_WPFD84KJqlyYeSy3U1qQwrrgG7MPUJl4ZnPreNISDUtHRC0qixM3sHeuWXZmbJyaiZVYuLaTeAPW3LvM5DSpztCmFptfNq6ruBtcbEH0d_b-rRz6Xs3rfICo7TJt-4oUMA7Ah2Ae0bPy6k-3soDPaHFJTdkKncydlG9ozL2OLmZM8VkT7UzgCnHCL-I9eJJVhoSqOOjU1c_w7vrhPXi2bDE7hDifEhSMTQgsyibHFWT9q-XWP7q1mKWYlh1EZ9yh6gbcoTAZZ-e3ByPPzUOncYY1mxYekhG9NSBje_6_fRTieCOX-KHvutBx44yOygnq6foSehrQf2Vv45-jLADkG4RRDuIgh3EIR_QRDuIgi3CHqBvn04Pn__kfjWGySHPeSCpIrpGPygVKwfwbPMcwHWvUypTrSEqI-liRaSm85nQmnYwuuy4FIqFXNVwh4gfom26qbWrxCOJYRJIslZKSmLyyI1pfGpzMEL92kZsV0UBxFlua9Lb37DJAsExHHmBJsZwWYRzUCwu4i0sy5dXZZ7xvMg_czHli5mzAAwd858_c8z36BHN8_CW7S1mC31HnqYrxbVfLbvkXUNl2KkKg |
| linkProvider | Elsevier |
| 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=A+double+auxiliary+optimization+constrained+multi-objective+evolutionary+algorithm&rft.jtitle=Mathematics+and+computers+in+simulation&rft.au=Yang%2C+Yongkuan&rft.au=Yan%2C+Bing&rft.au=Kong%2C+Xiangsong&rft.au=Zhao%2C+Jing&rft.date=2024-06-01&rft.pub=Elsevier+B.V&rft.issn=0378-4754&rft.eissn=1872-7166&rft.volume=220&rft.spage=567&rft.epage=579&rft_id=info:doi/10.1016%2Fj.matcom.2024.02.012&rft.externalDocID=S0378475424000624 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0378-4754&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0378-4754&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0378-4754&client=summon |