A reference vector based multiobjective evolutionary algorithm with Q-learning for operator adaptation
Maintaining a balance between convergence and diversity is a challenge for multiobjective evolutionary optimization. As crossover operators can affect the offspring distribution, an adaptive operator selection and reference vector based evolutionary algorithm (OVEA) for multiobjective optimization i...
Uložené v:
| Vydané v: | Swarm and evolutionary computation Ročník 76; s. 101225 |
|---|---|
| Hlavní autori: | , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Elsevier B.V
01.02.2023
|
| Predmet: | |
| ISSN: | 2210-6502 |
| On-line prístup: | Získať plný text |
| Tagy: |
Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
|
| Abstract | Maintaining a balance between convergence and diversity is a challenge for multiobjective evolutionary optimization. As crossover operators can affect the offspring distribution, an adaptive operator selection and reference vector based evolutionary algorithm (OVEA) for multiobjective optimization is proposed, where adaptive operator selection (AOS) adopts Q-learning to choose crossover operators, and the reference vector assists individual selection. To make the objective vectors as close to the true Pareto Front (PF) as possible and distributed uniformly along with PF, the different crossover operators and the association between reference vectors and individuals are used to drive the population evolution. The selection range of each reference vector is controlled by the associated population subset, from which an elite individual is selected. Observing the performance of offspring, the appropriate crossover operator is picked up by Q-learning. Finally, the proposed algorithm is evaluated on the benchmark problems with different objective number ranging from 2 to 10 and compared against the state-of-the-art algorithms. The experimental results show that OVEA has remarked advantages over the compared algorithms. |
|---|---|
| AbstractList | Maintaining a balance between convergence and diversity is a challenge for multiobjective evolutionary optimization. As crossover operators can affect the offspring distribution, an adaptive operator selection and reference vector based evolutionary algorithm (OVEA) for multiobjective optimization is proposed, where adaptive operator selection (AOS) adopts Q-learning to choose crossover operators, and the reference vector assists individual selection. To make the objective vectors as close to the true Pareto Front (PF) as possible and distributed uniformly along with PF, the different crossover operators and the association between reference vectors and individuals are used to drive the population evolution. The selection range of each reference vector is controlled by the associated population subset, from which an elite individual is selected. Observing the performance of offspring, the appropriate crossover operator is picked up by Q-learning. Finally, the proposed algorithm is evaluated on the benchmark problems with different objective number ranging from 2 to 10 and compared against the state-of-the-art algorithms. The experimental results show that OVEA has remarked advantages over the compared algorithms. |
| ArticleNumber | 101225 |
| Author | Jiao, Keming Xin, Bin Li, Li Chen, Jie |
| Author_xml | – sequence: 1 givenname: Keming orcidid: 0000-0003-0635-9578 surname: Jiao fullname: Jiao, Keming organization: School of Electronics and Information Engineering, Tongji University, Shanghai 201804, China – sequence: 2 givenname: Jie surname: Chen fullname: Chen, Jie organization: School of Electronics and Information Engineering, Tongji University, Shanghai 201804, China – sequence: 3 givenname: Bin surname: Xin fullname: Xin, Bin email: brucebin@bit.edu.cn organization: School of Automation, Beijing Institute of Technology, Beijing 100081, China – sequence: 4 givenname: Li surname: Li fullname: Li, Li organization: School of Electronics and Information Engineering, Tongji University, Shanghai 201804, China |
| BookMark | eNqFkMtOwzAQRb0oEqX0C9j4B1LscZwmCxZVxUuqhJBgbTl-FEdpXNlpKv4eh7BiAV6MpSudq5lzhWad7wxCN5SsKKHFbbOKZzP4FRCAMQHgMzQHoCQrOIFLtIyxIekVBDiv5shucDDWBNMpgwejeh9wLaPR-HBqe-frJmVuMDi1tqcUdDJ8YtnufXD9xwGf08SvWWtk6Fy3xzbx_miCHIuklsdejtA1urCyjWb58y_Q-8P92_Yp2708Pm83u0wxwvpMa6mgNpxrKNdKMsXKWitQUNY0t_m6YBYYLawsc16BriWsLeSVojmzmtacLRCbelXwMabLxDG4Q1pZUCJGQ6IR34bEaEhMhhJV_aKUm_bug3TtP-zdxJp01uBMEFG50aZ2IakT2rs_-S8sIIoX |
| CitedBy_id | crossref_primary_10_1016_j_matcom_2025_01_007 crossref_primary_10_1007_s11227_024_06258_8 crossref_primary_10_1038_s41598_024_52083_7 crossref_primary_10_1007_s10489_024_05906_z crossref_primary_10_26599_TST_2025_9010012 crossref_primary_10_1016_j_aej_2025_09_015 crossref_primary_10_1155_int_5521043 crossref_primary_10_1016_j_eswa_2024_125607 crossref_primary_10_1080_00207543_2024_2357740 crossref_primary_10_1109_TEVC_2023_3250350 crossref_primary_10_1109_TITS_2025_3538573 crossref_primary_10_1007_s10586_024_04381_y crossref_primary_10_3934_era_2025248 crossref_primary_10_1016_j_asoc_2025_112764 crossref_primary_10_1016_j_apenergy_2023_121332 crossref_primary_10_1007_s11227_024_06547_2 crossref_primary_10_1016_j_ins_2024_121397 crossref_primary_10_1016_j_swevo_2023_101397 crossref_primary_10_1109_TAI_2025_3545792 |
| Cites_doi | 10.1016/j.ins.2020.08.101 10.1109/TEVC.2018.2866854 10.1109/TEVC.2018.2848921 10.1109/TCYB.2018.2856208 10.1109/TEVC.2016.2549267 10.1109/4235.996017 10.1109/TSMC.2018.2818175 10.1109/TEVC.2012.2227145 10.1109/TCYB.2020.2977661 10.1109/TEVC.2015.2420112 10.1016/j.asoc.2018.10.028 10.3390/sym9100203 10.1137/S1052623496307510 10.1109/TEVC.2007.892759 10.1016/j.knosys.2015.12.022 10.1109/TEVC.2012.2204264 10.1016/j.ins.2017.10.037 10.3390/en9090678 10.1016/j.swevo.2019.06.009 10.1109/TEVC.2013.2281535 10.1109/TEVC.2020.3013290 10.1109/TEVC.2018.2865590 10.1016/j.swevo.2020.100669 10.1016/j.asoc.2022.108532 10.1109/TEVC.2017.2671462 10.1109/TEVC.2005.861417 10.1109/MCI.2019.2919398 10.1109/TEVC.2018.2882166 10.1109/TEVC.2016.2519378 10.1109/TEVC.2018.2836912 10.1145/3376916 10.1023/A:1008202821328 10.1016/j.knosys.2017.07.024 10.1109/TEVC.2013.2258025 10.1109/TCYB.2016.2638902 10.1109/TEVC.2019.2899030 10.1007/s10586-017-0793-8 10.1109/TEVC.2017.2749619 10.1007/s13748-018-0155-7 10.1162/EVCO_a_00109 10.1109/TEVC.2016.2587808 10.1016/j.ins.2021.06.054 |
| ContentType | Journal Article |
| Copyright | 2022 |
| Copyright_xml | – notice: 2022 |
| DBID | AAYXX CITATION |
| DOI | 10.1016/j.swevo.2022.101225 |
| DatabaseName | CrossRef |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Computer Science |
| ExternalDocumentID | 10_1016_j_swevo_2022_101225 S2210650222001912 |
| GroupedDBID | --K --M .~1 0R~ 1~. 1~5 4.4 457 4G. 5VS 7-5 8P~ AAAKF AABVA AACTN AAEDT AAEDW AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AARIN AATLK AAXUO AAYFN ABAOU ABBOA ABGRD ABMAC ABUCO ABXDB ABYKQ ACAZW ACDAQ ACGFS ACNNM ACRLP ACZNC ADBBV ADEZE ADMUD ADQTV ADTZH AEBSH AECPX AEKER AENEX AEQOU AFKWA AFTJW AFXIZ AGHFR AGUBO AGYEJ AHJVU AHZHX AIALX AIEXJ AIKHN AITUG AJBFU AJOXV ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AOUOD APLSM ARUGR AXJTR BJAXD BKOJK BLXMC CBWCG EBS EFJIC EFLBG EJD FDB FEDTE FIRID FNPLU FYGXN GBLVA GBOLZ HAMUX HVGLF HZ~ J1W JJJVA KOM M41 MHUIS MO0 N9A O-L O9- OAUVE P-8 P-9 PC. Q38 RIG ROL SDF SES SPC SPCBC SSA SSB SSD SST SSV SSW SSZ T5K ~G- AATTM AAXKI AAYWO AAYXX ABJNI ABWVN ACLOT ACRPL ACVFH ADCNI ADNMO AEIPS AEUPX AFJKZ AFPUW AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP CITATION EFKBS ~HD |
| ID | FETCH-LOGICAL-c303t-ddac2be55d287ca3c38bdc2c28b14f4763f2316fa84592dba27f249c143fd1b53 |
| ISICitedReferencesCount | 20 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000917443400001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 2210-6502 |
| IngestDate | Wed Nov 05 20:43:33 EST 2025 Tue Nov 18 22:30:36 EST 2025 Fri Feb 23 02:39:54 EST 2024 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Q-learning Adaptive operator selection Multiobjective evolutionary algorithm Reference vector |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c303t-ddac2be55d287ca3c38bdc2c28b14f4763f2316fa84592dba27f249c143fd1b53 |
| ORCID | 0000-0003-0635-9578 |
| ParticipantIDs | crossref_primary_10_1016_j_swevo_2022_101225 crossref_citationtrail_10_1016_j_swevo_2022_101225 elsevier_sciencedirect_doi_10_1016_j_swevo_2022_101225 |
| PublicationCentury | 2000 |
| PublicationDate | February 2023 2023-02-00 |
| PublicationDateYYYYMMDD | 2023-02-01 |
| PublicationDate_xml | – month: 02 year: 2023 text: February 2023 |
| PublicationDecade | 2020 |
| PublicationTitle | Swarm and evolutionary computation |
| PublicationYear | 2023 |
| Publisher | Elsevier B.V |
| Publisher_xml | – name: Elsevier B.V |
| References | Deb, Pratap, Agarwal, Meyarivan (bib0006) 2002; 6 Das, Dennis (bib0046) 1998; 8 Zou, Yen, Zhao (bib0029) 2021; 575 (ITEEE), DEStech Publications, 2019, pp. 67-76T. Truong Thanh, R. Wang, Li. Jia Hua, Multi-indicators multi-objective evolutionary algorithm with q-learning for real-world network optimization, DEStech Trans. Comput. Sci. Eng. (2019) (iteee). Wu, Wang, Zhang (bib0033) 2019 Mirjalili (bib0039) 2016; 96 Cheng, Jin, Olhofer, Sendhoff (bib0049) 2016; 20 Pamulapati, Mallipeddi, Suganthan (bib0016) 2018; 23 Santiago, Huacuja, Dorronsoro, Pecero, Santillan, Barbosa, Monterrubio (bib0048) 2014 Ke Shang, Hisao Ishibuchi, Linjun He, and Lie Meng Pang. A survey on the hypervolume indicator in evolutionary multi-objective optimization. Poap, Wozniak (bib0036) 2021; 166 Habib, Singh, Chugh, Ray, Miettinen (bib0050) 2019; 23 Kang, Song, Zhou, Li (bib0021) 2018; 49 Sun, Xue, Zhang, Yen (bib0001) 2018; 23 Chen, Li, Xin (bib0020) 2017; 21 Li, Zhang, Wang (bib0032) 2020; 51 Ning, Guo, Guo, Li, Yan (bib0027) 2018; 7 Deb, Joshi, Anand (bib0041) 2002; 1 Li, Chen, Li, Chen (bib0014) 2020; 55 Deb, Jain (bib0055) 2013; 18 Qiao, Zhou, Yang, Yang (bib0025) 2019; 74 Liu, Gong, Sun, Jin (bib0057) 2017; 47 Watkins, Dayan (bib0045) 1992; 8 Qi, Ma, Liu, Jiao, Sun, Wu (bib0023) 2014; 22 Deb (bib0058) 2001 Ma, Cheng, Wang, Huang, Shen, He, Shi (bib0030) 2017; 133 Yang, Li, Liu, Zheng (bib0009) 2013; 17 He, Zhou, Chen, Zhang (bib0062) 2018; 23 Li, Tang, Li, Yao (bib0061) 2016; 20 Zapotecas-Martinez, Coello, Aguirre, Tanaka (bib0051) 2018; 23 Khan, Zhang (bib0024) 2010 Chen, Wang (bib0042) 2017; 20 Tian, Cheng, Zhang, Li, Jin (bib0060) 2019; 14 Tian, Cheng, Zhang, Su, Jin (bib0011) 2018; 23 Xiang, Zhou, Li, Chen (bib0056) 2016; 21 Deb, Agrawal (bib0040) 1995; 9 Deb (bib0005) 2014 Wang, Li, Zhang, Hu, Shen (bib0047) 2019; 49 Storn, Price (bib0044) 1997; 11 Xu, Zeng, Zeng, Yen (bib0002) 2018; 49 25(1): 1-20, 2020. Tung Truong Thanh, Rui Wang, Jiahua Li, and Lianbo Ma. Multi-indicators multi-objective evolutionary algorithm with q-learning for real-world network optimization. Zeng, Gao, Li (bib0037) 2017 Zou, Yen, Tang, Wang (bib0028) 2021; 546 Huband, Hingston, Barone, While (bib0053) 2006; 10 Deb, Thiele, Laumanns, Zitzler (bib0052) 2002; 1 Zhang, Li (bib0019) 2007; 11 Zhang, Wu, Zhang, Wang (bib0034) 2022 Kukkonen, Lampinen (bib0003) 2007 Trivedi, Srinivasan, Sanyal, Ghosh (bib0022) 2016; 21 Chand, Wagner (bib0004) 2015; 20 He, Yen, Zhang (bib0008) 2013; 18 Zitzler, Laumanns, Thiele (bib0007) 2001; 103 Warid, Hizam, Mariun, Abdul-Wahab (bib0038) 2016; 9 Tsutsui, Yamamura, Higuchi (bib0043) 1999; 1 Falcón-Cardona, Coello (bib0013) 2020; 53 Tian, Cheng, Zhang, Cheng, Jin (bib0018) 2017; 22 Menchaca-Mendez, Coello (bib0015) 2015 Liu, Lu, Cheng, Shi (bib0026) 2019 Zhang, Zheng, Cheng, Qiu, Jin (bib0059) 2018; 427 Cui, Meng, Qiao (bib0017) 2022; 119 Yuan, Xu, Wang, Yao (bib0010) 2015; 20 Poap, Wozniak (bib0035) 2017; 9 Wang, Purshouse, Fleming (bib0054) 2012; 17 Zapotecas-Martinez (10.1016/j.swevo.2022.101225_bib0051) 2018; 23 Huband (10.1016/j.swevo.2022.101225_bib0053) 2006; 10 Khan (10.1016/j.swevo.2022.101225_bib0024) 2010 Yang (10.1016/j.swevo.2022.101225_bib0009) 2013; 17 Zeng (10.1016/j.swevo.2022.101225_bib0037) 2017 Zhang (10.1016/j.swevo.2022.101225_bib0019) 2007; 11 Chen (10.1016/j.swevo.2022.101225_bib0020) 2017; 21 Deb (10.1016/j.swevo.2022.101225_bib0006) 2002; 6 Cui (10.1016/j.swevo.2022.101225_bib0017) 2022; 119 Deb (10.1016/j.swevo.2022.101225_bib0040) 1995; 9 Ma (10.1016/j.swevo.2022.101225_bib0030) 2017; 133 Li (10.1016/j.swevo.2022.101225_bib0014) 2020; 55 Zou (10.1016/j.swevo.2022.101225_bib0029) 2021; 575 Zhang (10.1016/j.swevo.2022.101225_bib0059) 2018; 427 Tian (10.1016/j.swevo.2022.101225_bib0060) 2019; 14 Zou (10.1016/j.swevo.2022.101225_bib0028) 2021; 546 Qiao (10.1016/j.swevo.2022.101225_bib0025) 2019; 74 Deb (10.1016/j.swevo.2022.101225_bib0052) 2002; 1 Sun (10.1016/j.swevo.2022.101225_bib0001) 2018; 23 Habib (10.1016/j.swevo.2022.101225_bib0050) 2019; 23 Li (10.1016/j.swevo.2022.101225_bib0032) 2020; 51 Deb (10.1016/j.swevo.2022.101225_bib0055) 2013; 18 Zitzler (10.1016/j.swevo.2022.101225_bib0007) 2001; 103 Yuan (10.1016/j.swevo.2022.101225_bib0010) 2015; 20 10.1016/j.swevo.2022.101225_bib0012 Kukkonen (10.1016/j.swevo.2022.101225_bib0003) 2007 Falcón-Cardona (10.1016/j.swevo.2022.101225_bib0013) 2020; 53 Storn (10.1016/j.swevo.2022.101225_bib0044) 1997; 11 Watkins (10.1016/j.swevo.2022.101225_bib0045) 1992; 8 Poap (10.1016/j.swevo.2022.101225_bib0036) 2021; 166 Chen (10.1016/j.swevo.2022.101225_bib0042) 2017; 20 Liu (10.1016/j.swevo.2022.101225_bib0057) 2017; 47 Tsutsui (10.1016/j.swevo.2022.101225_bib0043) 1999; 1 Xu (10.1016/j.swevo.2022.101225_bib0002) 2018; 49 Wang (10.1016/j.swevo.2022.101225_bib0054) 2012; 17 Warid (10.1016/j.swevo.2022.101225_bib0038) 2016; 9 Santiago (10.1016/j.swevo.2022.101225_bib0048) 2014 Cheng (10.1016/j.swevo.2022.101225_bib0049) 2016; 20 Deb (10.1016/j.swevo.2022.101225_bib0041) 2002; 1 He (10.1016/j.swevo.2022.101225_bib0062) 2018; 23 Trivedi (10.1016/j.swevo.2022.101225_bib0022) 2016; 21 Liu (10.1016/j.swevo.2022.101225_bib0026) 2019 Deb (10.1016/j.swevo.2022.101225_bib0005) 2014 Tian (10.1016/j.swevo.2022.101225_bib0018) 2017; 22 Ning (10.1016/j.swevo.2022.101225_bib0027) 2018; 7 Poap (10.1016/j.swevo.2022.101225_bib0035) 2017; 9 Tian (10.1016/j.swevo.2022.101225_bib0011) 2018; 23 Wu (10.1016/j.swevo.2022.101225_bib0033) 2019 Pamulapati (10.1016/j.swevo.2022.101225_bib0016) 2018; 23 Li (10.1016/j.swevo.2022.101225_bib0061) 2016; 20 Menchaca-Mendez (10.1016/j.swevo.2022.101225_bib0015) 2015 Deb (10.1016/j.swevo.2022.101225_bib0058) 2001 Mirjalili (10.1016/j.swevo.2022.101225_bib0039) 2016; 96 Kang (10.1016/j.swevo.2022.101225_bib0021) 2018; 49 He (10.1016/j.swevo.2022.101225_bib0008) 2013; 18 Wang (10.1016/j.swevo.2022.101225_bib0047) 2019; 49 Qi (10.1016/j.swevo.2022.101225_bib0023) 2014; 22 Chand (10.1016/j.swevo.2022.101225_bib0004) 2015; 20 10.1016/j.swevo.2022.101225_bib0031 Xiang (10.1016/j.swevo.2022.101225_bib0056) 2016; 21 Zhang (10.1016/j.swevo.2022.101225_bib0034) 2022 Das (10.1016/j.swevo.2022.101225_bib0046) 1998; 8 |
| References_xml | – start-page: 3983 year: 2007 end-page: 3990 ident: bib0003 article-title: Ranking-dominance and many-objective optimization publication-title: Proceedings of the IEEE Congress on Evolutionary Computation – volume: 1 start-page: 825 year: 2002 end-page: 830 ident: bib0052 article-title: Scalable multi-objective optimization test problems publication-title: Proceedings of the Congress on Evolutionary Computation – volume: 18 start-page: 269 year: 2013 end-page: 285 ident: bib0008 article-title: Fuzzy-based pareto optimality for many-objective evolutionary algorithms publication-title: IEEE Trans. Evol. Comput. – volume: 20 start-page: 16 year: 2015 end-page: 37 ident: bib0010 article-title: A new dominance relation-based evolutionary algorithm for many-objective optimization publication-title: IEEE Trans. Evol. Comput. – volume: 8 start-page: 631 year: 1998 end-page: 657 ident: bib0046 article-title: Normal-boundary intersection: A new method for generating the pareto surface in nonlinear multicriteria optimization problems publication-title: SIAM J. Optim. – volume: 1 start-page: 657 year: 1999 end-page: 664 ident: bib0043 article-title: Multi-parent recombination with simplex crossover in real coded genetic algorithms publication-title: Proceedings of the 1st Annual Conference on Genetic and Evolutionary Computation – volume: 11 start-page: 712 year: 2007 end-page: 731 ident: bib0019 article-title: MOEA/D: a multiobjective evolutionary algorithm based on decomposition publication-title: IEEE Trans. Evol. Comput. – volume: 22 start-page: 231 year: 2014 end-page: 264 ident: bib0023 article-title: MOEA/D with adaptive weight adjustment publication-title: Evol. Comput. – volume: 11 start-page: 341 year: 1997 end-page: 359 ident: bib0044 article-title: Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces publication-title: J. Glob. Optim. – start-page: 403 year: 2014 end-page: 449 ident: bib0005 article-title: Multi-objective optimization publication-title: Search Methodologies – volume: 17 start-page: 474 year: 2012 end-page: 494 ident: bib0054 article-title: Preference-inspired coevolutionary algorithms for many-objective optimization publication-title: IEEE Trans. Evol. Comput. – volume: 166 year: 2021 ident: bib0036 article-title: Red fox optimization algorithm publication-title: Expert Syst. Appl. – year: 2001 ident: bib0058 article-title: Multiobjective Optimization Using Evolutionary Algorithms – reference: Ke Shang, Hisao Ishibuchi, Linjun He, and Lie Meng Pang. A survey on the hypervolume indicator in evolutionary multi-objective optimization. – reference: Tung Truong Thanh, Rui Wang, Jiahua Li, and Lianbo Ma. Multi-indicators multi-objective evolutionary algorithm with q-learning for real-world network optimization. – volume: 21 start-page: 131 year: 2016 end-page: 152 ident: bib0056 article-title: A vector angle-based evolutionary algorithm for unconstrained many-objective optimization publication-title: IEEE Trans. Evol. Comput. – volume: 14 start-page: 61 year: 2019 end-page: 74 ident: bib0060 article-title: Diversity assessment of multi-objective evolutionary algorithms: Performance metric and benchmark problems publication-title: IEEE Comput. Intell. Mag. – volume: 53 start-page: 1 year: 2020 end-page: 35 ident: bib0013 article-title: Indicator-based multi-objective evolutionary algorithms: a comprehensive survey publication-title: ACM Comput. Surv. (CSUR) – volume: 10 start-page: 477 year: 2006 end-page: 506 ident: bib0053 article-title: A review of multiobjective test problems and a scalable test problem toolkit publication-title: IEEE Trans. Evol. Comput. – volume: 49 start-page: 3968 year: 2018 end-page: 3979 ident: bib0002 article-title: An evolutionary algorithm based on minkowski distance for many-objective optimization publication-title: IEEE Trans. Cybern. – volume: 23 start-page: 331 year: 2018 end-page: 345 ident: bib0011 article-title: A strengthened dominance relation considering convergence and diversity for evolutionary many-objective optimization publication-title: IEEE Trans. Evol. Comput. – start-page: 1 year: 2010 end-page: 6 ident: bib0024 article-title: MOEA/D-DRA with two crossover operators publication-title: Proceedings of the UK Workshop On Computational Intelligence (UKCI) – volume: 546 start-page: 815 year: 2021 end-page: 834 ident: bib0028 article-title: A reinforcement learning approach for dynamic multi-objective optimization publication-title: Inf. Sci. – start-page: 624 year: 2017 end-page: 639 ident: bib0037 article-title: Whale swarm algorithm for function optimization publication-title: Proceedings of the International Conference on Intelligent Computing – volume: 9 start-page: 203 year: 2017 ident: bib0035 article-title: Polar bear optimization algorithm: Meta-heuristic with fast population movement and dynamic birth and death mechanism publication-title: Symmetry – volume: 103 year: 2001 ident: bib0007 article-title: SPEA2: improving the strength pareto evolutionary algorithm publication-title: TIK Rep. – volume: 9 start-page: 115 year: 1995 end-page: 148 ident: bib0040 article-title: Simulated binary crossover for continuous search space publication-title: Complex Syst. – volume: 7 start-page: 385 year: 2018 end-page: 398 ident: bib0027 article-title: Reinforcement learning aided parameter control in multi-objective evolutionary algorithm based on decomposition publication-title: Prog. Artif. Intell. – start-page: 575 year: 2019 end-page: 589 ident: bib0033 article-title: MODRL/D-AM: Multiobjective deep reinforcement learning algorithm using decomposition and attention model for multiobjective optimization publication-title: Proceedings of the International Symposium on Intelligence Computation and Applications – volume: 23 start-page: 130 year: 2018 end-page: 142 ident: bib0051 article-title: A review of features and limitations of existing scalable multiobjective test suites publication-title: IEEE Trans. Evol. Comput. – volume: 55 year: 2020 ident: bib0014 article-title: An enhanced-indicator based many-objective evolutionary algorithm with adaptive reference point publication-title: Swarm Evol. Comput. – volume: 17 start-page: 721 year: 2013 end-page: 736 ident: bib0009 article-title: A grid-based evolutionary algorithm for many-objective optimization publication-title: IEEE Trans. Evol. Comput. – volume: 9 start-page: 678 year: 2016 ident: bib0038 article-title: Optimal power flow using the jaya algorithm publication-title: Energies – volume: 51 start-page: 3103 year: 2020 end-page: 3114 ident: bib0032 article-title: Deep reinforcement learning for multiobjective optimization publication-title: IEEE Trans. Cybern. – volume: 20 start-page: 924 year: 2016 end-page: 938 ident: bib0061 article-title: Stochastic ranking algorithm for many-objective optimization based on multiple indicators publication-title: IEEE Trans. Evol. Comput. – volume: 20 start-page: 773 year: 2016 end-page: 791 ident: bib0049 article-title: A reference vector guided evolutionary algorithm for many-objective optimization publication-title: IEEE Trans. Evol. Comput. – volume: 18 start-page: 577 year: 2013 end-page: 601 ident: bib0055 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 Trans. Evol. Comput. – volume: 23 start-page: 748 year: 2018 end-page: 761 ident: bib0001 article-title: A new two-stage evolutionary algorithm for many-objective optimization publication-title: IEEE Trans. Evol. Comput. – volume: 21 start-page: 440 year: 2016 end-page: 462 ident: bib0022 article-title: A survey of multiobjective evolutionary algorithms based on decomposition publication-title: IEEE Trans. Evol. Comput. – volume: 575 start-page: 468 year: 2021 end-page: 484 ident: bib0029 article-title: Dynamic multiobjective optimization driven by inverse reinforcement learning publication-title: Inf. Sci. – volume: 1 start-page: 61 year: 2002 end-page: 66 ident: bib0041 article-title: Real-coded evolutionary algorithms with parent-centric recombination publication-title: Proceedings of the Congress on Evolutionary Computation – volume: 8 start-page: 279 year: 1992 end-page: 292 ident: bib0045 article-title: Q-learning publication-title: Int. J. Mach. Learn. Cybern. – volume: 23 start-page: 361 year: 2018 end-page: 375 ident: bib0062 article-title: Evolutionary many-objective optimization based on dynamical decomposition publication-title: IEEE Trans. Evol. Comput. – volume: 22 start-page: 609 year: 2017 end-page: 622 ident: bib0018 article-title: An indicator-based multiobjective evolutionary algorithm with reference point adaptation for better versatility publication-title: IEEE Trans. Evol. Comput. – volume: 21 start-page: 714 year: 2017 end-page: 730 ident: bib0020 article-title: DMOEA-ε: decomposition-based multiobjective evolutionary algorithm with the ε-constraint framework publication-title: IEEE Trans. Evol. Comput. – start-page: 815 year: 2019 end-page: 822 ident: bib0026 article-title: An adaptive online parameter control algorithm for particle swarm optimization based on reinforcement learning publication-title: Proceedings of the IEEE Congress on Evolutionary Computation (CEC) – volume: 49 start-page: 2416 year: 2018 end-page: 2423 ident: bib0021 article-title: A collaborative resource allocation strategy for decomposition-based multiobjective evolutionary algorithms publication-title: IEEE Trans. Syst. Man Cybern. Syst. – volume: 133 start-page: 278 year: 2017 end-page: 293 ident: bib0030 article-title: Cooperative two-engine multi-objective bee foraging algorithm with reinforcement learning publication-title: Knowl. Based Syst. – volume: 49 start-page: 220 year: 2019 end-page: 233 ident: bib0047 article-title: An adaptive weight vector guided evolutionary algorithm for preference-based multi-objective optimization publication-title: Swarm Evol. Comput. – volume: 20 start-page: 1247 year: 2017 end-page: 1257 ident: bib0042 article-title: Ant colony optimization with different crossover schemes for global optimization publication-title: Clust. Comput. – start-page: 453 year: 2014 end-page: 465 ident: bib0048 article-title: A survey of decomposition methods for multi-objective optimization publication-title: Recent Advances on Hybrid Approaches For Designing Intelligent Systems – reference: , 25(1): 1-20, 2020. – volume: 47 start-page: 2689 year: 2017 end-page: 2702 ident: bib0057 article-title: A many-objective evolutionary algorithm using a one-by-one selection strategy publication-title: IEEE Trans. Cybern. – year: 2022 ident: bib0034 article-title: Meta-learning-based deep reinforcement learning for multiobjective optimization problems publication-title: Proceedings of the Transactions on Neural Networks and Learning Systems – volume: 23 start-page: 1000 year: 2019 end-page: 1014 ident: bib0050 article-title: A multiple surrogate assisted decomposition-based evolutionary algorithm for expensive Multi/Many-objective optimization publication-title: IEEE Trans. Evol. Comput. – volume: 6 start-page: 182 year: 2002 end-page: 197 ident: bib0006 article-title: A fast and elitist multiobjective genetic algorithm: NSGA-II publication-title: IEEE Trans. Evol. Comput. – start-page: 947 year: 2015 end-page: 955 ident: bib0015 article-title: GDE-MOEA: A new moea based on the generational distance indicator and ε-dominance publication-title: Proceedings of the IEEE Congress on Evolutionary Computation – volume: 119 year: 2022 ident: bib0017 article-title: A multi-objective particle swarm optimization algorithm based on two-archive mechanism publication-title: Appl. Soft Comput. – volume: 74 start-page: 190 year: 2019 end-page: 205 ident: bib0025 article-title: A decomposition-based multiobjective evolutionary algorithm with angle-based adaptive penalty publication-title: Appl. Soft Comput. – volume: 96 start-page: 120 year: 2016 end-page: 133 ident: bib0039 article-title: SCA: a sine cosine algorithm for solving optimization problems publication-title: Knowl. Based Syst. – volume: 20 start-page: 35 year: 2015 end-page: 42 ident: bib0004 article-title: Evolutionary many-objective optimization: a quick-start guide publication-title: Surv. Oper. Res. Manag. Sci. – volume: 23 start-page: 346 year: 2018 end-page: 352 ident: bib0016 article-title: ISDE+ an indicator for multi and many-objective optimization publication-title: IEEE Trans. Evol. Comput. – reference: (ITEEE), DEStech Publications, 2019, pp. 67-76T. Truong Thanh, R. Wang, Li. Jia Hua, Multi-indicators multi-objective evolutionary algorithm with q-learning for real-world network optimization, DEStech Trans. Comput. Sci. Eng. (2019) (iteee). – volume: 427 start-page: 63 year: 2018 end-page: 76 ident: bib0059 article-title: A competitive mechanism based multi-objective particle swarm optimizer with fast convergence publication-title: Inf. Sci. – start-page: 403 year: 2014 ident: 10.1016/j.swevo.2022.101225_bib0005 article-title: Multi-objective optimization – volume: 546 start-page: 815 year: 2021 ident: 10.1016/j.swevo.2022.101225_bib0028 article-title: A reinforcement learning approach for dynamic multi-objective optimization publication-title: Inf. Sci. doi: 10.1016/j.ins.2020.08.101 – volume: 23 start-page: 331 issue: 2 year: 2018 ident: 10.1016/j.swevo.2022.101225_bib0011 article-title: A strengthened dominance relation considering convergence and diversity for evolutionary many-objective optimization publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2018.2866854 – volume: 20 start-page: 35 issue: 2 year: 2015 ident: 10.1016/j.swevo.2022.101225_bib0004 article-title: Evolutionary many-objective optimization: a quick-start guide publication-title: Surv. Oper. Res. Manag. Sci. – volume: 23 start-page: 346 issue: 2 year: 2018 ident: 10.1016/j.swevo.2022.101225_bib0016 article-title: ISDE+ an indicator for multi and many-objective optimization publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2018.2848921 – volume: 49 start-page: 3968 issue: 11 year: 2018 ident: 10.1016/j.swevo.2022.101225_bib0002 article-title: An evolutionary algorithm based on minkowski distance for many-objective optimization publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2018.2856208 – volume: 20 start-page: 924 issue: 6 year: 2016 ident: 10.1016/j.swevo.2022.101225_bib0061 article-title: Stochastic ranking algorithm for many-objective optimization based on multiple indicators publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2016.2549267 – start-page: 3983 year: 2007 ident: 10.1016/j.swevo.2022.101225_bib0003 article-title: Ranking-dominance and many-objective optimization – volume: 8 start-page: 279 issue: 3-4 year: 1992 ident: 10.1016/j.swevo.2022.101225_bib0045 article-title: Q-learning publication-title: Int. J. Mach. Learn. Cybern. – volume: 9 start-page: 115 issue: 2 year: 1995 ident: 10.1016/j.swevo.2022.101225_bib0040 article-title: Simulated binary crossover for continuous search space publication-title: Complex Syst. – volume: 6 start-page: 182 issue: 2 year: 2002 ident: 10.1016/j.swevo.2022.101225_bib0006 article-title: A fast and elitist multiobjective genetic algorithm: NSGA-II publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/4235.996017 – volume: 21 start-page: 440 issue: 3 year: 2016 ident: 10.1016/j.swevo.2022.101225_bib0022 article-title: A survey of multiobjective evolutionary algorithms based on decomposition publication-title: IEEE Trans. Evol. Comput. – volume: 1 start-page: 825 year: 2002 ident: 10.1016/j.swevo.2022.101225_bib0052 article-title: Scalable multi-objective optimization test problems – volume: 49 start-page: 2416 issue: 12 year: 2018 ident: 10.1016/j.swevo.2022.101225_bib0021 article-title: A collaborative resource allocation strategy for decomposition-based multiobjective evolutionary algorithms publication-title: IEEE Trans. Syst. Man Cybern. Syst. doi: 10.1109/TSMC.2018.2818175 – volume: 17 start-page: 721 issue: 5 year: 2013 ident: 10.1016/j.swevo.2022.101225_bib0009 article-title: A grid-based evolutionary algorithm for many-objective optimization publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2012.2227145 – year: 2022 ident: 10.1016/j.swevo.2022.101225_bib0034 article-title: Meta-learning-based deep reinforcement learning for multiobjective optimization problems – volume: 51 start-page: 3103 issue: 6 year: 2020 ident: 10.1016/j.swevo.2022.101225_bib0032 article-title: Deep reinforcement learning for multiobjective optimization publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2020.2977661 – volume: 20 start-page: 16 issue: 1 year: 2015 ident: 10.1016/j.swevo.2022.101225_bib0010 article-title: A new dominance relation-based evolutionary algorithm for many-objective optimization publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2015.2420112 – volume: 74 start-page: 190 year: 2019 ident: 10.1016/j.swevo.2022.101225_bib0025 article-title: A decomposition-based multiobjective evolutionary algorithm with angle-based adaptive penalty publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2018.10.028 – volume: 9 start-page: 203 issue: 10 year: 2017 ident: 10.1016/j.swevo.2022.101225_bib0035 article-title: Polar bear optimization algorithm: Meta-heuristic with fast population movement and dynamic birth and death mechanism publication-title: Symmetry doi: 10.3390/sym9100203 – volume: 8 start-page: 631 issue: 3 year: 1998 ident: 10.1016/j.swevo.2022.101225_bib0046 article-title: Normal-boundary intersection: A new method for generating the pareto surface in nonlinear multicriteria optimization problems publication-title: SIAM J. Optim. doi: 10.1137/S1052623496307510 – volume: 11 start-page: 712 issue: 6 year: 2007 ident: 10.1016/j.swevo.2022.101225_bib0019 article-title: MOEA/D: a multiobjective evolutionary algorithm based on decomposition publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2007.892759 – volume: 96 start-page: 120 year: 2016 ident: 10.1016/j.swevo.2022.101225_bib0039 article-title: SCA: a sine cosine algorithm for solving optimization problems publication-title: Knowl. Based Syst. doi: 10.1016/j.knosys.2015.12.022 – start-page: 453 year: 2014 ident: 10.1016/j.swevo.2022.101225_bib0048 article-title: A survey of decomposition methods for multi-objective optimization – volume: 17 start-page: 474 issue: 4 year: 2012 ident: 10.1016/j.swevo.2022.101225_bib0054 article-title: Preference-inspired coevolutionary algorithms for many-objective optimization publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2012.2204264 – volume: 427 start-page: 63 year: 2018 ident: 10.1016/j.swevo.2022.101225_bib0059 article-title: A competitive mechanism based multi-objective particle swarm optimizer with fast convergence publication-title: Inf. Sci. doi: 10.1016/j.ins.2017.10.037 – volume: 9 start-page: 678 issue: 9 year: 2016 ident: 10.1016/j.swevo.2022.101225_bib0038 article-title: Optimal power flow using the jaya algorithm publication-title: Energies doi: 10.3390/en9090678 – volume: 1 start-page: 657 year: 1999 ident: 10.1016/j.swevo.2022.101225_bib0043 article-title: Multi-parent recombination with simplex crossover in real coded genetic algorithms – volume: 49 start-page: 220 year: 2019 ident: 10.1016/j.swevo.2022.101225_bib0047 article-title: An adaptive weight vector guided evolutionary algorithm for preference-based multi-objective optimization publication-title: Swarm Evol. Comput. doi: 10.1016/j.swevo.2019.06.009 – volume: 18 start-page: 577 issue: 4 year: 2013 ident: 10.1016/j.swevo.2022.101225_bib0055 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 Trans. Evol. Comput. doi: 10.1109/TEVC.2013.2281535 – ident: 10.1016/j.swevo.2022.101225_bib0012 doi: 10.1109/TEVC.2020.3013290 – year: 2001 ident: 10.1016/j.swevo.2022.101225_bib0058 – volume: 23 start-page: 361 issue: 3 year: 2018 ident: 10.1016/j.swevo.2022.101225_bib0062 article-title: Evolutionary many-objective optimization based on dynamical decomposition publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2018.2865590 – volume: 55 year: 2020 ident: 10.1016/j.swevo.2022.101225_bib0014 article-title: An enhanced-indicator based many-objective evolutionary algorithm with adaptive reference point publication-title: Swarm Evol. Comput. doi: 10.1016/j.swevo.2020.100669 – volume: 119 year: 2022 ident: 10.1016/j.swevo.2022.101225_bib0017 article-title: A multi-objective particle swarm optimization algorithm based on two-archive mechanism publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2022.108532 – volume: 21 start-page: 714 issue: 5 year: 2017 ident: 10.1016/j.swevo.2022.101225_bib0020 article-title: DMOEA-ε: decomposition-based multiobjective evolutionary algorithm with the ε-constraint framework publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2017.2671462 – start-page: 575 year: 2019 ident: 10.1016/j.swevo.2022.101225_bib0033 article-title: MODRL/D-AM: Multiobjective deep reinforcement learning algorithm using decomposition and attention model for multiobjective optimization – volume: 10 start-page: 477 issue: 5 year: 2006 ident: 10.1016/j.swevo.2022.101225_bib0053 article-title: A review of multiobjective test problems and a scalable test problem toolkit publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2005.861417 – volume: 14 start-page: 61 issue: 3 year: 2019 ident: 10.1016/j.swevo.2022.101225_bib0060 article-title: Diversity assessment of multi-objective evolutionary algorithms: Performance metric and benchmark problems publication-title: IEEE Comput. Intell. Mag. doi: 10.1109/MCI.2019.2919398 – volume: 23 start-page: 748 issue: 5 year: 2018 ident: 10.1016/j.swevo.2022.101225_bib0001 article-title: A new two-stage evolutionary algorithm for many-objective optimization publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2018.2882166 – start-page: 947 year: 2015 ident: 10.1016/j.swevo.2022.101225_bib0015 article-title: GDE-MOEA: A new moea based on the generational distance indicator and ε-dominance – volume: 166 year: 2021 ident: 10.1016/j.swevo.2022.101225_bib0036 article-title: Red fox optimization algorithm publication-title: Expert Syst. Appl. – volume: 20 start-page: 773 issue: 5 year: 2016 ident: 10.1016/j.swevo.2022.101225_bib0049 article-title: A reference vector guided evolutionary algorithm for many-objective optimization publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2016.2519378 – start-page: 1 year: 2010 ident: 10.1016/j.swevo.2022.101225_bib0024 article-title: MOEA/D-DRA with two crossover operators – volume: 23 start-page: 130 issue: 1 year: 2018 ident: 10.1016/j.swevo.2022.101225_bib0051 article-title: A review of features and limitations of existing scalable multiobjective test suites publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2018.2836912 – volume: 103 year: 2001 ident: 10.1016/j.swevo.2022.101225_bib0007 article-title: SPEA2: improving the strength pareto evolutionary algorithm publication-title: TIK Rep. – start-page: 624 year: 2017 ident: 10.1016/j.swevo.2022.101225_bib0037 article-title: Whale swarm algorithm for function optimization – volume: 53 start-page: 1 issue: 2 year: 2020 ident: 10.1016/j.swevo.2022.101225_bib0013 article-title: Indicator-based multi-objective evolutionary algorithms: a comprehensive survey publication-title: ACM Comput. Surv. (CSUR) doi: 10.1145/3376916 – volume: 11 start-page: 341 issue: 4 year: 1997 ident: 10.1016/j.swevo.2022.101225_bib0044 article-title: Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces publication-title: J. Glob. Optim. doi: 10.1023/A:1008202821328 – volume: 133 start-page: 278 year: 2017 ident: 10.1016/j.swevo.2022.101225_bib0030 article-title: Cooperative two-engine multi-objective bee foraging algorithm with reinforcement learning publication-title: Knowl. Based Syst. doi: 10.1016/j.knosys.2017.07.024 – volume: 18 start-page: 269 issue: 2 year: 2013 ident: 10.1016/j.swevo.2022.101225_bib0008 article-title: Fuzzy-based pareto optimality for many-objective evolutionary algorithms publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2013.2258025 – volume: 47 start-page: 2689 issue: 9 year: 2017 ident: 10.1016/j.swevo.2022.101225_bib0057 article-title: A many-objective evolutionary algorithm using a one-by-one selection strategy publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2016.2638902 – volume: 23 start-page: 1000 issue: 6 year: 2019 ident: 10.1016/j.swevo.2022.101225_bib0050 article-title: A multiple surrogate assisted decomposition-based evolutionary algorithm for expensive Multi/Many-objective optimization publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2019.2899030 – volume: 20 start-page: 1247 issue: 2 year: 2017 ident: 10.1016/j.swevo.2022.101225_bib0042 article-title: Ant colony optimization with different crossover schemes for global optimization publication-title: Clust. Comput. doi: 10.1007/s10586-017-0793-8 – ident: 10.1016/j.swevo.2022.101225_bib0031 – volume: 22 start-page: 609 issue: 4 year: 2017 ident: 10.1016/j.swevo.2022.101225_bib0018 article-title: An indicator-based multiobjective evolutionary algorithm with reference point adaptation for better versatility publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2017.2749619 – volume: 7 start-page: 385 issue: 4 year: 2018 ident: 10.1016/j.swevo.2022.101225_bib0027 article-title: Reinforcement learning aided parameter control in multi-objective evolutionary algorithm based on decomposition publication-title: Prog. Artif. Intell. doi: 10.1007/s13748-018-0155-7 – volume: 22 start-page: 231 issue: 2 year: 2014 ident: 10.1016/j.swevo.2022.101225_bib0023 article-title: MOEA/D with adaptive weight adjustment publication-title: Evol. Comput. doi: 10.1162/EVCO_a_00109 – start-page: 815 year: 2019 ident: 10.1016/j.swevo.2022.101225_bib0026 article-title: An adaptive online parameter control algorithm for particle swarm optimization based on reinforcement learning – volume: 1 start-page: 61 year: 2002 ident: 10.1016/j.swevo.2022.101225_bib0041 article-title: Real-coded evolutionary algorithms with parent-centric recombination – volume: 21 start-page: 131 issue: 1 year: 2016 ident: 10.1016/j.swevo.2022.101225_bib0056 article-title: A vector angle-based evolutionary algorithm for unconstrained many-objective optimization publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2016.2587808 – volume: 575 start-page: 468 year: 2021 ident: 10.1016/j.swevo.2022.101225_bib0029 article-title: Dynamic multiobjective optimization driven by inverse reinforcement learning publication-title: Inf. Sci. doi: 10.1016/j.ins.2021.06.054 |
| SSID | ssj0000602559 |
| Score | 2.3907943 |
| Snippet | Maintaining a balance between convergence and diversity is a challenge for multiobjective evolutionary optimization. As crossover operators can affect the... |
| SourceID | crossref elsevier |
| SourceType | Enrichment Source Index Database Publisher |
| StartPage | 101225 |
| SubjectTerms | Adaptive operator selection Multiobjective evolutionary algorithm Q-learning Reference vector |
| Title | A reference vector based multiobjective evolutionary algorithm with Q-learning for operator adaptation |
| URI | https://dx.doi.org/10.1016/j.swevo.2022.101225 |
| Volume | 76 |
| WOSCitedRecordID | wos000917443400001&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 issn: 2210-6502 databaseCode: AIEXJ dateStart: 20110301 customDbUrl: isFulltext: true dateEnd: 99991231 titleUrlDefault: https://www.sciencedirect.com omitProxy: false ssIdentifier: ssj0000602559 providerName: Elsevier |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1LT9tAEF5VoQcutDyqUijaAzdjlOzasX2MEFXhgFollXKz9mXqKNhREgI_n9mXkzQIQSUuVmRl187Ol9mZ2Zn5EDoVYKUK8JNDpZvcRZFqh6wTFWHBue7WTinpSEM2kdzcpMNh9stVl8wMnUBSVenjYzZ5V1HDPRC2Lp19g7ibSeEGfAahwxXEDtdXCb4XNNQhwcLE5AO9VUmbO1jzkVVxgVq419B5c2x8W0_L-d87G5j9HY59yESnIdYTZU7jAybZZOXs3hm1_Qc2tUwba3MKQxixdtJ_XbLaVgPd-S3TpBa4CpGyQdnQ0ciXy4whW8ZdroYpCPWZzT52tlE_o1UcAYczBBtxTR9bPpgN1W6jDKPz2QP8FnDsCdH3iC2b_qdndl9PrOclOmUs0yzUWySJM1B7W72ry-F1E4Zrd41TpSkI_bv43lQmC3Djac_bLys2yeAz2nHOBO5ZEOyiD6raQ588UQd2ensfFT3cYAJbTGCDCbyOCbwqP9xgAmtM4CUmMGACe0zgJSYO0J8fl4OLn6Ej2AgFWC7zUEomCFdxLMFvFowKmnIpiCAph_9rBFtPAeZ_t2BpFGdEckaSAtx1ATZ2ITs8pl9Qq6or9RXBs2hBBUskbApg4rAUFrUrOGWUyDij6hARv2y5cN3nNQnKOPdphqPcrHWu1zq3a32IzppBE9t85eWvd708cmc_WrswBwy9NPDb_w48QttLrB-j1nx6r76jj2IxL2fTE4e1JynRmi8 |
| 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+reference+vector+based+multiobjective+evolutionary+algorithm+with+Q-learning+for+operator+adaptation&rft.jtitle=Swarm+and+evolutionary+computation&rft.au=Jiao%2C+Keming&rft.au=Chen%2C+Jie&rft.au=Xin%2C+Bin&rft.au=Li%2C+Li&rft.date=2023-02-01&rft.pub=Elsevier+B.V&rft.issn=2210-6502&rft.volume=76&rft_id=info:doi/10.1016%2Fj.swevo.2022.101225&rft.externalDocID=S2210650222001912 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2210-6502&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2210-6502&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2210-6502&client=summon |