Automatic Component-Wise Design of Multiobjective Evolutionary Algorithms
Multiobjective evolutionary algorithms (MOEAs) are typically proposed, studied, and applied as monolithic blocks with a few numerical parameters that need to be set. Few works have studied how the algorithmic components of these evolutionary algorithms can be classified and combined to produce new a...
Saved in:
| Published in: | IEEE transactions on evolutionary computation Vol. 20; no. 3; pp. 403 - 417 |
|---|---|
| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
New York
IEEE
01.06.2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects: | |
| ISSN: | 1089-778X, 1941-0026 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Abstract | Multiobjective evolutionary algorithms (MOEAs) are typically proposed, studied, and applied as monolithic blocks with a few numerical parameters that need to be set. Few works have studied how the algorithmic components of these evolutionary algorithms can be classified and combined to produce new algorithmic designs. The motivation for studies of this latter type stem from the development of flexible software frameworks and the usage of automatic algorithm configuration methods to find novel algorithm designs. In this paper, we propose an MOEA template and a new conceptual view of its components that surpasses existing frameworks in both number of algorithms that can be instantiated from the template and flexibility to produce novel algorithmic designs. We empirically demonstrate the flexibility of our proposed framework by automatically designing MOEAs for continuous and combinatorial optimization problems. The automatically designed algorithms are often able to outperform six traditional MOEAs from the literature, even after tuning their numerical parameters. |
|---|---|
| AbstractList | Multiobjective evolutionary algorithms (MOEAs) are typically proposed, studied, and applied as monolithic blocks with a few numerical parameters that need to be set. Few works have studied how the algorithmic components of these evolutionary algorithms can be classified and combined to produce new algorithmic designs. The motivation for studies of this latter type stem from the development of flexible software frameworks and the usage of automatic algorithm configuration methods to find novel algorithm designs. In this paper, we propose anMOEA template and a new conceptual view of its components that surpasses existing frameworks in both number of algorithms that can be instantiated from the template and flexibility to produce novel algorithmic designs. We empirically demonstrate the flexibility of our proposed framework by automatically designing MOEAs for continuous and combinatorial optimization problems. The automatically designed algorithms are often able to outperform six traditional MOEAs from the literature, even after tuning their numerical parameters. Multiobjective evolutionary algorithms (MOEAs) are typically proposed, studied, and applied as monolithic blocks with a few numerical parameters that need to be set. Few works have studied how the algorithmic components of these evolutionary algorithms can be classified and combined to produce new algorithmic designs. The motivation for studies of this latter type stem from the development of flexible software frameworks and the usage of automatic algorithm configuration methods to find novel algorithm designs. In this paper, we propose an MOEA template and a new conceptual view of its components that surpasses existing frameworks in both number of algorithms that can be instantiated from the template and flexibility to produce novel algorithmic designs. We empirically demonstrate the flexibility of our proposed framework by automatically designing MOEAs for continuous and combinatorial optimization problems. The automatically designed algorithms are often able to outperform six traditional MOEAs from the literature, even after tuning their numerical parameters. |
| Author | Lopez-Ibanez, Manuel Bezerra, Leonardo C. T. Stutzle, Thomas |
| Author_xml | – sequence: 1 givenname: Leonardo C. T. surname: Bezerra fullname: Bezerra, Leonardo C. T. email: lteonaci@ulb.ac.be organization: IRIDIA Lab., Univ. Libre de Bruxelles, Brussels, Belgium – sequence: 2 givenname: Manuel surname: Lopez-Ibanez fullname: Lopez-Ibanez, Manuel email: manuel.lopez-ibanez@ulb.ac.be organization: IRIDIA Lab., Univ. Libre de Bruxelles, Brussels, Belgium – sequence: 3 givenname: Thomas surname: Stutzle fullname: Stutzle, Thomas email: stuetzle@ulb.ac.be organization: IRIDIA Lab., Univ. Libre de Bruxelles, Brussels, Belgium |
| BookMark | eNp9kD9PwzAQxS1UJNrCB0AskVhYUnxOHMdjVQpUKmIpfzbLdZziKolL7FTi2-OoFUMHpjud3ru79xuhQWMbjdA14AkA5ver-ftsQjDQCUlZCjQ_Q0PgKcQYk2wQepzzmLH88wKNnNtiDCkFPkSLaedtLb1R0czWu7C08fGHcTp60M5smsiW0UtXeWPXW6282etovrdVFwaNbH-iabWxrfFftbtE56WsnL461jF6e5yvZs_x8vVpMZsuY5Vk3Mc6U1xCAVRRlkqSAC9kmWpV8JxhlUia5ZxgSoCQrMwLKWmpJF0zmpQyVYlOxujusHfX2u9OOy9q45SuKtlo2zkBOaEpz3IMQXp7It3arm3CdwIYJ4xnnJGggoNKtda5Vpdi15o6hBOARQ9X9HBFD1cc4QYPO_Eo42UPxbfSVP86bw5Oo7X-u8RCWsZp8gsf9olf |
| CODEN | ITEVF5 |
| CitedBy_id | crossref_primary_10_1016_j_ins_2023_119547 crossref_primary_10_1016_j_asoc_2020_106851 crossref_primary_10_1111_sjos_12786 crossref_primary_10_1007_s10664_019_09761_2 crossref_primary_10_1145_3612933 crossref_primary_10_1109_TAI_2020_3022339 crossref_primary_10_1162_evco_a_00241 crossref_primary_10_1162_evco_a_00263 crossref_primary_10_1109_TEVC_2015_2512930 crossref_primary_10_1162_evco_a_00245 crossref_primary_10_1016_j_ejor_2024_06_001 crossref_primary_10_1007_s10994_022_06212_w crossref_primary_10_1016_j_swevo_2024_101838 crossref_primary_10_1162_evco_a_00217 crossref_primary_10_1007_s11721_023_00227_2 crossref_primary_10_3390_electronics12224639 crossref_primary_10_1155_2022_4544818 crossref_primary_10_1016_j_eswa_2023_121431 crossref_primary_10_1016_j_eswa_2023_121674 crossref_primary_10_1016_j_ejor_2020_07_059 crossref_primary_10_1016_j_asoc_2019_03_044 crossref_primary_10_1016_j_ins_2017_02_034 crossref_primary_10_1162_artl_a_00402 crossref_primary_10_1109_TEVC_2022_3211336 crossref_primary_10_1109_MCI_2017_2742868 crossref_primary_10_1016_j_aei_2025_103428 crossref_primary_10_1016_j_asoc_2023_110187 crossref_primary_10_1016_j_eswa_2022_117667 crossref_primary_10_1016_j_cor_2018_12_015 crossref_primary_10_1016_j_eswa_2021_115493 crossref_primary_10_1016_j_swevo_2020_100670 crossref_primary_10_1109_TEVC_2023_3314152 crossref_primary_10_1007_s11721_017_0131_z crossref_primary_10_1109_TSMC_2018_2858843 crossref_primary_10_3390_mca27060103 crossref_primary_10_3390_pr12050869 crossref_primary_10_1016_j_swevo_2023_101248 |
| Cites_doi | 10.1007/978-3-642-19893-9_4 10.1007/978-3-642-01020-0_33 10.1109/TEVC.2013.2248159 10.1109/TEVC.2013.2281535 10.1007/978-3-319-10762-2_50 10.1162/EVCO_a_00105 10.1162/106365600568202 10.1016/j.ejor.2006.08.008 10.1162/EVCO_a_00009 10.1007/1-84628-137-7_6 10.1162/106365600568167 10.1109/CEC.2000.870274 10.1007/978-3-642-01020-0_18 10.1109/TEVC.2011.2182651 10.1007/978-3-319-09584-4_16 10.1162/evco.2007.15.1.1 10.1109/TEVC.2009.2016569 10.1109/TEVC.2003.810758 10.1109/CEC.2005.1554717 10.1016/j.cor.2010.10.008 10.1109/4235.996017 10.1109/TEVC.2007.892759 10.1162/106365600568158 10.1145/2076450.2076469 10.1504/IJAISC.2014.059280 10.1109/TEVC.2005.861417 10.1007/s10589-014-9644-1 10.1007/3-540-36970-8_35 10.1007/978-3-642-17144-4_2 10.1287/ijoc.1070.0258 10.1016/j.ejor.2010.07.023 |
| ContentType | Journal Article |
| Copyright | Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2016 |
| Copyright_xml | – notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2016 |
| DBID | 97E RIA RIE AAYXX CITATION 7SC 7SP 8FD JQ2 L7M L~C L~D F28 FR3 |
| DOI | 10.1109/TEVC.2015.2474158 |
| DatabaseName | IEEE All-Society Periodicals Package (ASPP) 2005–Present IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE Electronic Library (IEL) CrossRef Computer and Information Systems Abstracts Electronics & Communications Abstracts Technology Research Database ProQuest Computer Science Collection Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional ANTE: Abstracts in New Technology & Engineering Engineering Research Database |
| DatabaseTitle | CrossRef Technology Research Database Computer and Information Systems Abstracts – Academic Electronics & Communications Abstracts ProQuest Computer Science Collection Computer and Information Systems Abstracts Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Professional Engineering Research Database ANTE: Abstracts in New Technology & Engineering |
| DatabaseTitleList | Technology Research Database Technology Research Database |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE/IET Electronic Library url: https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering Statistics Computer Science |
| EISSN | 1941-0026 |
| EndPage | 417 |
| ExternalDocumentID | 4073927921 10_1109_TEVC_2015_2474158 7226795 |
| Genre | orig-research |
| GrantInformation_xml | – fundername: Belgian F.R.S.-FNRS – fundername: COMEX Project (P7/36) within the Interuniversity Attraction Poles Programme of the Belgian Science Policy Office |
| GroupedDBID | -~X .DC 0R~ 29I 4.4 5GY 5VS 6IF 6IK 6IL 6IN 97E AAJGR AARMG AASAJ AAWTH ABAZT ABJNI ABQJQ ABVLG ACGFO ACGFS ACIWK ADZIZ AENEX AETIX AGQYO AGSQL AHBIQ AI. AIBXA AKJIK AKQYR ALLEH ALMA_UNASSIGNED_HOLDINGS ATWAV BEFXN BFFAM BGNUA BKEBE BPEOZ CHZPO CS3 EBS EJD HZ~ H~9 IEGSK IFIPE IFJZH IPLJI JAVBF LAI M43 O9- OCL P2P PQQKQ RIA RIE RIL RNS TN5 VH1 AAYXX CITATION 7SC 7SP 8FD JQ2 L7M L~C L~D F28 FR3 |
| ID | FETCH-LOGICAL-c369t-e6c9a1d15c574a2319daf4ecd9870c3a568920521226f8daa5fca5b753fa4c3e3 |
| IEDL.DBID | RIE |
| ISICitedReferencesCount | 74 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000377620600006&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1089-778X |
| IngestDate | Sun Sep 28 08:49:49 EDT 2025 Sun Nov 09 08:04:23 EST 2025 Sat Nov 29 03:13:47 EST 2025 Tue Nov 18 22:38:11 EST 2025 Tue Aug 26 16:42:57 EDT 2025 |
| IsDoiOpenAccess | false |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 3 |
| Keywords | multiobjective optimization Automatic algorithm configuration permutation flow shop problem (PFSP) evolutionary algorithms |
| Language | English |
| License | https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c369t-e6c9a1d15c574a2319daf4ecd9870c3a568920521226f8daa5fca5b753fa4c3e3 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| OpenAccessLink | https://www.research.manchester.ac.uk/portal/en/publications/automatic-componentwise-design-of-multiobjective-evolutionary-algorithms(fd746474-ac14-4def-be96-dcd3ece5fc4c).html |
| PQID | 1792796972 |
| PQPubID | 85418 |
| PageCount | 15 |
| ParticipantIDs | crossref_primary_10_1109_TEVC_2015_2474158 proquest_miscellaneous_1825496801 proquest_journals_1792796972 crossref_citationtrail_10_1109_TEVC_2015_2474158 ieee_primary_7226795 |
| PublicationCentury | 2000 |
| PublicationDate | 2016-June 2016-6-00 20160601 |
| PublicationDateYYYYMMDD | 2016-06-01 |
| PublicationDate_xml | – month: 06 year: 2016 text: 2016-June |
| PublicationDecade | 2010 |
| PublicationPlace | New York |
| PublicationPlace_xml | – name: New York |
| PublicationTitle | IEEE transactions on evolutionary computation |
| PublicationTitleAbbrev | TEVC |
| PublicationYear | 2016 |
| Publisher | IEEE The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher_xml | – name: IEEE – name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| References | ref35 ref13 fawcett (ref39) 2013 ref12 ref37 ref15 ref36 ref14 ref31 ref11 zitzler (ref4) 2004 ref32 ref10 ref2 ref19 ref18 biscani (ref16) 2010 zitzler (ref3) 2002 birattari (ref34) 2002 deb (ref7) 2001 ref24 ref23 ref26 ref25 igel (ref17) 2008; 9 ref20 ref42 coello (ref8) 2007 ref41 ref22 ref44 ref43 (ref38) 2015 lópez-ibáñez (ref21) 2011 ref28 ref27 ref29 ref9 birattari (ref33) 2004 bezerra (ref30) 2015 ref6 fonseca (ref1) 1993 ref5 ref40 |
| References_xml | – year: 2007 ident: ref8 publication-title: Evolutionary Algorithms for Solving Multi-Objective Problems – ident: ref26 doi: 10.1007/978-3-642-19893-9_4 – ident: ref43 doi: 10.1007/978-3-642-01020-0_33 – ident: ref37 doi: 10.1109/TEVC.2013.2248159 – ident: ref44 doi: 10.1109/TEVC.2013.2281535 – start-page: 832 year: 2004 ident: ref4 article-title: Indicator-based selection in multiobjective search publication-title: Parallel Problem Solving from Nature-PPSN VII – ident: ref23 doi: 10.1007/978-3-319-10762-2_50 – start-page: 11 year: 2002 ident: ref34 article-title: A racing algorithm for configuring metaheuristics publication-title: Proc GECCO – ident: ref36 doi: 10.1162/EVCO_a_00105 – ident: ref9 doi: 10.1162/106365600568202 – year: 2015 ident: ref38 publication-title: Journal of Heuristic Policies on Heuristic Search Research – ident: ref6 doi: 10.1016/j.ejor.2006.08.008 – ident: ref5 doi: 10.1162/EVCO_a_00009 – year: 2004 ident: ref33 article-title: The problem of tuning metaheuristics as seen from a machine learning perspective – ident: ref10 doi: 10.1007/1-84628-137-7_6 – ident: ref24 doi: 10.1162/106365600568167 – year: 2011 ident: ref21 article-title: The irace package: Iterated race for automatic algorithm configuration – ident: ref18 doi: 10.1109/CEC.2000.870274 – ident: ref13 doi: 10.1007/978-3-642-01020-0_18 – ident: ref20 doi: 10.1109/TEVC.2011.2182651 – ident: ref12 doi: 10.1007/978-3-319-09584-4_16 – ident: ref40 doi: 10.1162/evco.2007.15.1.1 – ident: ref19 doi: 10.1109/TEVC.2009.2016569 – ident: ref28 doi: 10.1109/TEVC.2003.810758 – ident: ref41 doi: 10.1109/CEC.2005.1554717 – ident: ref32 doi: 10.1016/j.cor.2010.10.008 – ident: ref2 doi: 10.1109/4235.996017 – ident: ref25 doi: 10.1109/TEVC.2007.892759 – year: 2015 ident: ref30 publication-title: Automatic Component-Wise Design Of Multi-Objective Evolutionary Algorithms – ident: ref11 doi: 10.1162/106365600568158 – ident: ref35 doi: 10.1145/2076450.2076469 – start-page: 95 year: 2002 ident: ref3 article-title: SPEA2: Improving the strength Pareto evolutionary algorithm for multiobjective optimization publication-title: Proc EUROGEN – year: 2010 ident: ref16 article-title: A global optimisation toolbox for massively parallel engineering optimisation publication-title: Proc ICAT – ident: ref29 doi: 10.1504/IJAISC.2014.059280 – start-page: 416 year: 1993 ident: ref1 article-title: Genetic algorithms for multiobjective optimization: Formulation, discussion and generalization publication-title: Proc ICGA – ident: ref22 doi: 10.1109/TEVC.2005.861417 – start-page: 123 year: 2013 ident: ref39 article-title: Analysing differences between algorithm configurations through ablation publication-title: Proc MIC – ident: ref42 doi: 10.1007/s10589-014-9644-1 – ident: ref15 doi: 10.1007/3-540-36970-8_35 – ident: ref27 doi: 10.1007/978-3-642-17144-4_2 – ident: ref31 doi: 10.1287/ijoc.1070.0258 – ident: ref14 doi: 10.1016/j.ejor.2010.07.023 – volume: 9 start-page: 993 year: 2008 ident: ref17 article-title: Shark publication-title: J Mach Learn Res – year: 2001 ident: ref7 publication-title: Multi-Objective Optimization Using Evolutionary Algorithms |
| SSID | ssj0014519 |
| Score | 2.5072727 |
| Snippet | Multiobjective evolutionary algorithms (MOEAs) are typically proposed, studied, and applied as monolithic blocks with a few numerical parameters that need to... |
| SourceID | proquest crossref ieee |
| SourceType | Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 403 |
| SubjectTerms | Algorithm design and analysis Algorithms automatic algorithm configuration Automation Combinatorial analysis Evolutionary algorithms Evolutionary computation Flexibility Genetic algorithms Mathematical models Measurement Multiobjective optimization Optimization permutation flowshop problem Proposals Sociology Software algorithms Statistics Tuning |
| Title | Automatic Component-Wise Design of Multiobjective Evolutionary Algorithms |
| URI | https://ieeexplore.ieee.org/document/7226795 https://www.proquest.com/docview/1792796972 https://www.proquest.com/docview/1825496801 |
| Volume | 20 |
| WOSCitedRecordID | wos000377620600006&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVIEE databaseName: IEEE/IET Electronic Library customDbUrl: eissn: 1941-0026 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0014519 issn: 1089-778X databaseCode: RIE dateStart: 19970101 isFulltext: true titleUrlDefault: https://ieeexplore.ieee.org/ providerName: IEEE |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1Jb9QwFH5qRxzKoYUpiCkDMlJPVdMmdmznHUdlKrhUHLrMLbIdG4rKBM1Sqf--tuOJqIqQuEWKHVv5_Da_DeDQ8lKzgpWZ0TnLSos0Q1HojDquELnRqtCx2YS8uKhmM_y2Bcd9Loy1Ngaf2ZPwGH35TWvW4arsVHpdQSLfhm0pZZer1XsMQpmULpgevcZYzZIHs8jx9HJ6fRaCuPgJLYMArZ7IoNhU5RknjuLlfO__NvYKdpMaSSYd7q9hy86HsLdp0UASxQ7h5R_1BoewE1TLrjLzPnydrFdtLNhKwrx27pfIbm6XlnyOUR2kdSSm57b6Z8cVyfQ-HVS1eCCTu-_t4nb149fyDVydTy_PvmSpsUJmmMBVZoVBVTQFN1yWymt42ChXWtOgp17DFBcV0pjVS4WrGqW4M4prb9k4VRpm2VsYzP223gExVlgpUOVOBZerQkc1qzRlwomikG4E-eZX1yZVHQ_NL-7qaH3kWAd06oBOndAZwVE_5XdXcuNfg_cDHP3AhMQIxhs860SUy9rzHipRoKQj-NS_9uQUfCRqbtu1HxMtZuHl9sHfv_wedvz6oosWG8NgtVjbD_DC3Hv4Fh_jmXwEiq7fHg |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1Lb9QwEB6VgkR7oLAFsVDASJwQaRO_kjmu2q1aUVYcFthbZDs2FJUN2kel_ntsxxsVgZC4Rco4sfJ5XpkXwBsruGYF45nROcu4RZqhLHRGnVCIwmhV6DhsopxMqtkMP27Bu74Wxlobk8_sYbiMsfymNevwq-yo9LZCieIO3BWc06Kr1upjBqFRSpdOj95mrGYphlnkeDQdfz4OaVzikPKgQqvftFAcq_KHLI4K5nTv_7b2EB4kQ5KMOuQfwZadD2BvM6SBJJ4dwO6tjoMD2AnGZdebeR_OR-tVG1u2krCunftXZF8ul5acxLwO0joSC3Rb_b2Ti2R8nY6qWtyQ0dXXdnG5-vZj-Rg-nY6nx2dZGq2QGSZxlVlpUBVNIYwoufI2HjbKcWsa9PxrmBKyQhrreql0VaOUcEYJ7X0bp7hhlj2B7bnf1lMgxkpbSlS5UyHoqtBRzSpNmXSyKEo3hHzzqWuT-o6H8RdXdfQ_cqwDOnVAp07oDOFtv-Rn13TjX8T7AY6eMCExhIMNnnViy2XtpQ8tUWJJh_C6v-0ZKkRJ1Ny2a08TfWbpNfezvz_5Fdw_m364qC_OJ--fw47fi-xyxw5ge7VY2xdwz1x7KBcv4_n8BUqi4mU |
| 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=Automatic+Component-Wise+Design+of+Multiobjective+Evolutionary+Algorithms&rft.jtitle=IEEE+transactions+on+evolutionary+computation&rft.au=Bezerra%2C+Leonardo+C+T&rft.au=Lopez-Ibanez%2C+Manuel&rft.au=Stutzle%2C+Thomas&rft.date=2016-06-01&rft.pub=The+Institute+of+Electrical+and+Electronics+Engineers%2C+Inc.+%28IEEE%29&rft.issn=1089-778X&rft.eissn=1941-0026&rft.volume=20&rft.issue=3&rft.spage=403&rft_id=info:doi/10.1109%2FTEVC.2015.2474158&rft.externalDBID=NO_FULL_TEXT&rft.externalDocID=4073927921 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1089-778X&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1089-778X&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1089-778X&client=summon |