{"id":"https://openalex.org/W3178628565","doi":"https://doi.org/10.1109/tevc.2021.3095313","title":"Transfer Learning-Based Parallel Evolutionary Algorithm Framework for Bilevel Optimization","display_name":"Transfer Learning-Based Parallel Evolutionary Algorithm Framework for Bilevel Optimization","publication_year":2021,"publication_date":"2021-07-07","ids":{"openalex":"https://openalex.org/W3178628565","doi":"https://doi.org/10.1109/tevc.2021.3095313","mag":"3178628565"},"language":"en","primary_location":{"id":"doi:10.1109/tevc.2021.3095313","doi":"https://doi.org/10.1109/tevc.2021.3095313","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tevc.2021.3095313","pdf_url":null,"source":{"id":"https://openalex.org/S93787993","display_name":"IEEE Transactions on Evolutionary Computation","issn_l":"1089-778X","issn":["1089-778X","1941-0026"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","ccf-b","cwts-core","dongbi-a","fnege-4","jufo-3","norway-2","poland-200","russia-white-list-1"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Evolutionary Computation","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100333550","display_name":"Lei Chen","orcid":"https://orcid.org/0000-0003-1423-3481","observed_orcids":["https://orcid.org/0000-0003-1423-3481"]},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Chen","raw_affiliation_strings":["School of Applied Mathematics, Guangdong University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-1423-3481","affiliations":[{"raw_affiliation_string":"School of Applied Mathematics, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100610638","display_name":"Hai\u2010Lin Liu","orcid":"https://orcid.org/0000-0003-2276-1938","observed_orcids":["https://orcid.org/0000-0003-2276-1938"]},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hai-Lin Liu","raw_affiliation_strings":["School of Applied Mathematics, Guangdong University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-2276-1938","affiliations":[{"raw_affiliation_string":"School of Applied Mathematics, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025285243","display_name":"Kay Chen Tan","orcid":"https://orcid.org/0000-0002-6802-2463","observed_orcids":["https://orcid.org/0000-0002-6802-2463"]},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Kay Chen Tan","raw_affiliation_strings":["Department of Computing, Hong Kong Polytechnic University, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0002-6802-2463","affiliations":[{"raw_affiliation_string":"Department of Computing, Hong Kong Polytechnic University, Hong Kong","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100343450","display_name":"Ke Li","orcid":"https://orcid.org/0000-0001-7200-4244","observed_orcids":["https://orcid.org/0000-0001-7200-4244"]},"institutions":[{"id":"https://openalex.org/I23923803","display_name":"University of Exeter","ror":"https://ror.org/03yghzc09","country_code":"GB","type":"education","lineage":["https://openalex.org/I23923803"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ke Li","raw_affiliation_strings":["Department of Computer Science, University of Exeter, Exeter, U.K"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Exeter, Exeter, U.K","institution_ids":["https://openalex.org/I23923803"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":1.8778,"has_fulltext":false,"cited_by_count":56,"citation_normalized_percentile":{"value":0.86906461,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":87,"max":100},"biblio":{"volume":"26","issue":"1","first_page":"115","last_page":"129"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9648000001907349,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9648000001907349,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.023000000044703484,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.007199999876320362,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/bi-level-optimization","display_name":"bi-level optimization","score":0.9990000128746033},{"id":"https://openalex.org/keywords/transfer-learning","display_name":"transfer learning","score":0.8050000071525574},{"id":"https://openalex.org/keywords/parallel-evolutionary-algorithms","display_name":"parallel evolutionary algorithms","score":0.890999972820282},{"id":"https://openalex.org/keywords/covariance-matrix-adaptation-evolutionary-strategy","display_name":"covariance matrix adaptation evolutionary strategy","score":0.8019999861717224},{"id":"https://openalex.org/keywords/differential-evolution","display_name":"differential evolution","score":0.9990000128746033}],"concepts":[{"id":"https://openalex.org/C3309286","wikidata":"https://www.wikidata.org/wiki/Q4907693","display_name":"Bilevel optimization","level":3,"score":0.721062183380127},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.6628051996231079},{"id":"https://openalex.org/C205555498","wikidata":"https://www.wikidata.org/wiki/Q505588","display_name":"CMA-ES","level":4,"score":0.649870753288269},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6369838118553162},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.634853720664978},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6250544190406799},{"id":"https://openalex.org/C105902424","wikidata":"https://www.wikidata.org/wiki/Q1197129","display_name":"Evolutionary computation","level":2,"score":0.4873846173286438},{"id":"https://openalex.org/C207002847","wikidata":"https://www.wikidata.org/wiki/Q2912857","display_name":"Evolution strategy","level":3,"score":0.4778327941894531},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.44262754917144775},{"id":"https://openalex.org/C74750220","wikidata":"https://www.wikidata.org/wiki/Q2662197","display_name":"Differential evolution","level":2,"score":0.4124700725078583},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3793433904647827},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32954657077789307},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28691554069519043},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tevc.2021.3095313","doi":"https://doi.org/10.1109/tevc.2021.3095313","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tevc.2021.3095313","pdf_url":null,"source":{"id":"https://openalex.org/S93787993","display_name":"IEEE Transactions on Evolutionary Computation","issn_l":"1089-778X","issn":["1089-778X","1941-0026"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","ccf-b","cwts-core","dongbi-a","fnege-4","jufo-3","norway-2","poland-200","russia-white-list-1"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Evolutionary Computation","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G2615012307","display_name":null,"funder_award_id":"62076056","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3446298049","display_name":null,"funder_award_id":"2020A1515011500","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G6708675553","display_name":null,"funder_award_id":"MR/S017062/1","funder_id":"https://openalex.org/F4320314731","funder_display_name":"UK Research and Innovation"},{"id":"https://openalex.org/G6854851746","display_name":null,"funder_award_id":"62006044","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8622129177","display_name":null,"funder_award_id":"EPSRC 2404317","funder_id":"https://openalex.org/F4320314731","funder_display_name":"UK Research and Innovation"}],"funders":[{"id":"https://openalex.org/F4320314731","display_name":"UK Research and Innovation","ror":"https://ror.org/001aqnf71"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W397669542","https://openalex.org/W1493761729","https://openalex.org/W1511522460","https://openalex.org/W1752034067","https://openalex.org/W1972038842","https://openalex.org/W1974952991","https://openalex.org/W1992590811","https://openalex.org/W1999037958","https://openalex.org/W2005629858","https://openalex.org/W2007103412","https://openalex.org/W2018705062","https://openalex.org/W2030667419","https://openalex.org/W2032195237","https://openalex.org/W2035452420","https://openalex.org/W2035893651","https://openalex.org/W2038456806","https://openalex.org/W2056468324","https://openalex.org/W2060743072","https://openalex.org/W2061233843","https://openalex.org/W2065534296","https://openalex.org/W2071082401","https://openalex.org/W2079104779","https://openalex.org/W2084575232","https://openalex.org/W2093966662","https://openalex.org/W2112036188","https://openalex.org/W2130364940","https://openalex.org/W2134230680","https://openalex.org/W2144051602","https://openalex.org/W2154062181","https://openalex.org/W2163194391","https://openalex.org/W2165698076","https://openalex.org/W2322565568","https://openalex.org/W2329255878","https://openalex.org/W2521809336","https://openalex.org/W2557096003","https://openalex.org/W2586101872","https://openalex.org/W2587953039","https://openalex.org/W2614367549","https://openalex.org/W2745612259","https://openalex.org/W2809148884","https://openalex.org/W2884332575","https://openalex.org/W2921407359","https://openalex.org/W2965341466","https://openalex.org/W2969112071","https://openalex.org/W3010117582","https://openalex.org/W3010321770","https://openalex.org/W3011220450","https://openalex.org/W3016550207","https://openalex.org/W3017105781","https://openalex.org/W3094604376"],"related_works":["https://openalex.org/W4380302376","https://openalex.org/W3191451262","https://openalex.org/W4413022284","https://openalex.org/W4315778176","https://openalex.org/W2809148884","https://openalex.org/W1762936176","https://openalex.org/W4407128832","https://openalex.org/W2521809336","https://openalex.org/W4294811404","https://openalex.org/W4417116161"],"abstract_inverted_index":{"Evolutionary":[0],"algorithms":[1,164],"(EAs)":[2],"have":[3],"been":[4],"recognized":[5],"as":[6,123],"a":[7,42,59,73,79],"promising":[8],"approach":[9],"for":[10,49],"bilevel":[11,50,140,162],"optimization.":[12,51,130],"However,":[13],"the":[14,27,31,55,77,87,103,105,109,116,120,124,147,150,167,172],"population-based":[15],"characteristic":[16],"of":[17,30,34,57,61,89,102,137,149,158,171],"EAs":[18],"largely":[19],"influences":[20],"their":[21],"efficiency":[22,170],"and":[23,115,146,169],"effectiveness":[24,88,168],"due":[25],"to":[26,85,156,165],"nested":[28],"structure":[29],"two":[32,100,135,151],"levels":[33],"optimization":[35,141,163],"problems.":[36],"In":[37,52,76,96],"this":[38,53],"article,":[39],"we":[40,98],"propose":[41],"transfer":[43,80],"learning-based":[44],"parallel":[45,74],"EA":[46],"(TLEA)":[47],"framework":[48],"framework,":[54],"task":[56],"optimizing":[58],"set":[60],"lower":[62,91,128],"level":[63,68,92,129],"problems":[64,143],"parameterized":[65],"by":[66],"upper":[67],"variables":[69],"is":[70,83,154],"conducted":[71],"in":[72,127],"manner.":[75],"meanwhile,":[78],"learning":[81],"strategy":[82,114],"developed":[84],"improve":[86],"each":[90],"search":[93],"(LLS)":[94],"process.":[95],"practice,":[97],"implement":[99],"versions":[101],"TLEA:":[104],"first":[106],"version":[107,118],"uses":[108,119],"covariance":[110],"matrix":[111],"adaptation":[112],"evolutionary":[113,125,161],"second":[117],"differential":[121],"evolution":[122],"operator":[126],"The":[131],"experimental":[132],"studies":[133],"on":[134],"sets":[136],"widely":[138],"used":[139],"benchmark":[142],"are":[144],"conducted,":[145],"performance":[148],"TLEA":[152],"implementations":[153],"compared":[155],"that":[157],"four":[159],"well-established":[160],"verify":[166],"proposed":[173],"algorithm":[174],"framework.":[175]},"counts_by_year":[{"year":2026,"cited_by_count":13},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2026-11-12T12:28:57.059296","created_date":"2021-07-19T00:00:00"}