{"id":"https://openalex.org/W2557848526","doi":"https://doi.org/10.1109/cec.2016.7748321","title":"Testing an evolutionary portfolio algorithm on the CEC2016 real-parameter single objective optimization","display_name":"Testing an evolutionary portfolio algorithm on the CEC2016 real-parameter single objective optimization","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2557848526","doi":"https://doi.org/10.1109/cec.2016.7748321","mag":"2557848526"},"language":"en","primary_location":{"id":"doi:10.1109/cec.2016.7748321","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2016.7748321","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Congress on Evolutionary Computation (CEC)","raw_type":"proceedings-article"},"type":"article","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/A5019215450","display_name":"Junyan Yi","orcid":"https://orcid.org/0000-0002-8819-8642"},"institutions":[{"id":"https://openalex.org/I62853816","display_name":"Beijing University of Civil Engineering and Architecture","ror":"https://ror.org/02yj0p855","country_code":"CN","type":"education","lineage":["https://openalex.org/I62853816"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Junyan Yi","raw_affiliation_strings":["Department of Computer Science and Technology, Beijing University of Civil Engineering and Architecture, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Beijing University of Civil Engineering and Architecture, Beijing, China","institution_ids":["https://openalex.org/I62853816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034648573","display_name":"Zheng He","orcid":"https://orcid.org/0000-0002-7700-0901"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"He Zheng","raw_affiliation_strings":["Department of Information Renmin University of China, Multimedia Computing Lab, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Information Renmin University of China, Multimedia Computing Lab, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002627939","display_name":"Gang Yang","orcid":"https://orcid.org/0000-0003-0765-6769"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Yang","raw_affiliation_strings":["Department of Information Renmin University of China, Multimedia Computing Lab, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Information Renmin University of China, Multimedia Computing Lab, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5019215450"],"corresponding_institution_ids":["https://openalex.org/I62853816"],"apc_list":null,"apc_paid":null,"fwci":0.857,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.84598826,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"4996","last_page":"5001"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9998999834060669,"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":0.9997000098228455,"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/component","display_name":"Component (thermodynamics)","score":0.7253249883651733},{"id":"https://openalex.org/keywords/portfolio","display_name":"Portfolio","score":0.7222885489463806},{"id":"https://openalex.org/keywords/evolutionary-algorithm","display_name":"Evolutionary algorithm","score":0.6826100945472717},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6381955742835999},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5384146571159363},{"id":"https://openalex.org/keywords/portfolio-optimization","display_name":"Portfolio optimization","score":0.5300110578536987},{"id":"https://openalex.org/keywords/evolutionary-computation","display_name":"Evolutionary computation","score":0.5154600739479065},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4911195933818817},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4867863357067108},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.47042346000671387},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2864348888397217},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.25787076354026794},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.05767810344696045}],"concepts":[{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.7253249883651733},{"id":"https://openalex.org/C2780821815","wikidata":"https://www.wikidata.org/wiki/Q5340806","display_name":"Portfolio","level":2,"score":0.7222885489463806},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.6826100945472717},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6381955742835999},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5384146571159363},{"id":"https://openalex.org/C202655437","wikidata":"https://www.wikidata.org/wiki/Q7231728","display_name":"Portfolio optimization","level":3,"score":0.5300110578536987},{"id":"https://openalex.org/C105902424","wikidata":"https://www.wikidata.org/wiki/Q1197129","display_name":"Evolutionary computation","level":2,"score":0.5154600739479065},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4911195933818817},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4867863357067108},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.47042346000671387},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2864348888397217},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25787076354026794},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.05767810344696045},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cec.2016.7748321","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2016.7748321","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Congress on Evolutionary Computation (CEC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W102487131","https://openalex.org/W1595159159","https://openalex.org/W1779658280","https://openalex.org/W2018719085","https://openalex.org/W2018971911","https://openalex.org/W2059328013","https://openalex.org/W2069650035","https://openalex.org/W2097571405","https://openalex.org/W2100274914","https://openalex.org/W2123682012","https://openalex.org/W2129724855","https://openalex.org/W2151554678","https://openalex.org/W2152195021","https://openalex.org/W2182761707","https://openalex.org/W2336687883","https://openalex.org/W2505770036","https://openalex.org/W2828451641","https://openalex.org/W4285719527","https://openalex.org/W4324106947","https://openalex.org/W6667948199","https://openalex.org/W6682642761","https://openalex.org/W6686280248","https://openalex.org/W6702989015"],"related_works":["https://openalex.org/W1986311305","https://openalex.org/W4360613713","https://openalex.org/W3125148470","https://openalex.org/W2768197547","https://openalex.org/W2055959038","https://openalex.org/W4206877017","https://openalex.org/W4225528185","https://openalex.org/W4327779378","https://openalex.org/W4297582752","https://openalex.org/W4285805405"],"abstract_inverted_index":{"In":[0,49],"order":[1],"to":[2,19,43,82],"take":[3],"advantages":[4],"of":[5,14,24,39,68],"evolutionary":[6,40],"algorithms":[7,41],"inspired":[8],"by":[9],"different":[10],"biological":[11],"evolutions,":[12],"varieties":[13],"approaches":[15],"have":[16],"been":[17],"proposed":[18,85],"combine":[20],"them":[21,25],"together.":[22],"One":[23],"is":[26,80,88,103],"the":[27,46,66,72,76,91],"portfolio":[28,38,86],"approach,":[29,51],"which":[30],"keeps":[31],"choosing":[32],"a":[33,37],"component":[34,53,73],"algorithm":[35,54,74],"from":[36],"(EAs)":[42],"run":[44],"during":[45],"optimizing":[47],"process.":[48],"our":[50],"each":[52,69],"has":[55],"its":[56],"own":[57],"population":[58],"and":[59],"runs":[60],"independently":[61],"without":[62],"information":[63],"exchange.":[64],"At":[65],"beginning":[67],"generation,":[70],"only":[71],"with":[75],"best":[77],"predicted":[78],"performance":[79],"allowed":[81],"run.":[83],"The":[84,98],"approach":[87],"tested":[89],"on":[90],"CEC2016":[92],"real-parameter":[93],"single":[94],"objective":[95],"optimization":[96],"benchmarks.":[97],"results":[99],"show":[100],"that":[101],"it":[102],"competitive.":[104]},"counts_by_year":[{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
