{"id":"https://openalex.org/W4226420899","doi":"https://doi.org/10.1109/ccis53392.2021.9754528","title":"A Classification-based Mixture-of-Kriging Assisted Evolutionary Algorithm for Expensive Many-objective Optimization","display_name":"A Classification-based Mixture-of-Kriging Assisted Evolutionary Algorithm for Expensive Many-objective Optimization","publication_year":2021,"publication_date":"2021-11-07","ids":{"openalex":"https://openalex.org/W4226420899","doi":"https://doi.org/10.1109/ccis53392.2021.9754528"},"language":"en","primary_location":{"id":"doi:10.1109/ccis53392.2021.9754528","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccis53392.2021.9754528","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 7th International Conference on Cloud Computing and Intelligent Systems (CCIS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5069212056","display_name":"Gaoli Kang","orcid":"https://orcid.org/0009-0000-0070-3871"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gaoli Kang","raw_affiliation_strings":["Shenzhen University,Shenzhen,China,518000"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen University,Shenzhen,China,518000","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061705030","display_name":"Xunfeng Wu","orcid":"https://orcid.org/0000-0002-8225-6565"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xunfeng Wu","raw_affiliation_strings":["Shenzhen University,Shenzhen,China,518000"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen University,Shenzhen,China,518000","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066935890","display_name":"Qiuzhen Lin","orcid":"https://orcid.org/0000-0003-2415-0401"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiuzhen Lin","raw_affiliation_strings":["Shenzhen University,Shenzhen,China,518000"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen University,Shenzhen,China,518000","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"134","last_page":"138"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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/T11798","display_name":"Optimal Experimental Design Methods","score":0.9866999983787537,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9697999954223633,"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/benchmark","display_name":"Benchmark (surveying)","score":0.8038144707679749},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.7147175073623657},{"id":"https://openalex.org/keywords/evolutionary-algorithm","display_name":"Evolutionary algorithm","score":0.7065190076828003},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6633516550064087},{"id":"https://openalex.org/keywords/surrogate-model","display_name":"Surrogate model","score":0.5078220963478088},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4959345757961273},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4778699278831482},{"id":"https://openalex.org/keywords/optimization-algorithm","display_name":"Optimization algorithm","score":0.46516066789627075},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46437138319015503},{"id":"https://openalex.org/keywords/multi-objective-optimization","display_name":"Multi-objective optimization","score":0.4413797855377197},{"id":"https://openalex.org/keywords/evolutionary-computation","display_name":"Evolutionary computation","score":0.4301775097846985},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3578096628189087},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23223549127578735}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.8038144707679749},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.7147175073623657},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.7065190076828003},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6633516550064087},{"id":"https://openalex.org/C131675550","wikidata":"https://www.wikidata.org/wiki/Q7646884","display_name":"Surrogate model","level":2,"score":0.5078220963478088},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4959345757961273},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4778699278831482},{"id":"https://openalex.org/C2987595161","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Optimization algorithm","level":2,"score":0.46516066789627075},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46437138319015503},{"id":"https://openalex.org/C68781425","wikidata":"https://www.wikidata.org/wiki/Q2052203","display_name":"Multi-objective optimization","level":2,"score":0.4413797855377197},{"id":"https://openalex.org/C105902424","wikidata":"https://www.wikidata.org/wiki/Q1197129","display_name":"Evolutionary computation","level":2,"score":0.4301775097846985},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3578096628189087},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23223549127578735},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccis53392.2021.9754528","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccis53392.2021.9754528","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 7th International Conference on Cloud Computing and Intelligent Systems (CCIS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W265409813","https://openalex.org/W1514363319","https://openalex.org/W1585939719","https://openalex.org/W2000836282","https://openalex.org/W2011174137","https://openalex.org/W2022485595","https://openalex.org/W2098907614","https://openalex.org/W2105245738","https://openalex.org/W2126105956","https://openalex.org/W2128357515","https://openalex.org/W2143381319","https://openalex.org/W2546299924","https://openalex.org/W2785722638","https://openalex.org/W2890351024","https://openalex.org/W4239510810","https://openalex.org/W4249517230","https://openalex.org/W6609867952","https://openalex.org/W6635097213","https://openalex.org/W6754573523"],"related_works":["https://openalex.org/W2931365531","https://openalex.org/W3014573403","https://openalex.org/W4381941132","https://openalex.org/W2084593435","https://openalex.org/W2114881872","https://openalex.org/W2198736978","https://openalex.org/W3084133043","https://openalex.org/W2139145565","https://openalex.org/W2905297725","https://openalex.org/W2060305711"],"abstract_inverted_index":{"Surrogate-assisted":[0],"evolutionary":[1],"algorithms":[2],"(SAEAs)":[3],"have":[4],"been":[5],"widely":[6],"used":[7],"to":[8,30,56,76],"solve":[9,31],"expensive":[10],"optimization":[11],"problems":[12],"(EOPs).":[13],"However,":[14],"most":[15],"studies":[16],"only":[17],"focus":[18],"on":[19,97],"solving":[20],"single":[21],"or":[22],"multiobjective":[23],"EOPs.":[24,63],"The":[25],"study":[26],"of":[27,100],"using":[28,51],"SAEAs":[29,96],"many-objective":[32],"EOPs":[33],"has":[34],"not":[35],"received":[36],"much":[37],"attention.":[38],"To":[39],"fill":[40],"this":[41,44,65],"research":[42],"gap,":[43],"paper":[45],"presents":[46],"a":[47,54,67,98],"new":[48],"SAEA":[49],"by":[50],"mixture-of-Kriging":[52],"as":[53],"surrogate":[55],"approximate":[57],"the":[58,78,84,94],"objective":[59],"values":[60],"in":[61,90],"many-objecitve":[62],"In":[64],"algorithm,":[66],"fitness-based":[68],"classification":[69],"method":[70],"is":[71,87],"employed":[72],"for":[73],"choosing":[74],"data":[75],"train":[77],"models.":[79],"Experimental":[80],"results":[81],"demonstrate":[82],"that":[83],"proposed":[85],"algorithm":[86],"very":[88],"promising":[89],"performance":[91],"comparison":[92],"with":[93],"state-of-the-art":[95],"number":[99],"benchmark":[101],"problems.":[102]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}