{"id":"https://openalex.org/W2911578165","doi":"https://doi.org/10.1109/ssci.2018.8628707","title":"A Parametric Study of Crossover Operators in Multi-objective Evolutionary Algorithm","display_name":"A Parametric Study of Crossover Operators in Multi-objective Evolutionary Algorithm","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2911578165","doi":"https://doi.org/10.1109/ssci.2018.8628707","mag":"2911578165"},"language":"en","primary_location":{"id":"doi:10.1109/ssci.2018.8628707","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci.2018.8628707","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Symposium Series on Computational Intelligence (SSCI)","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/A5006325506","display_name":"Katsuhiro Sekine","orcid":"https://orcid.org/0000-0001-6964-6318"},"institutions":[{"id":"https://openalex.org/I161296585","display_name":"Tokyo University of Science","ror":"https://ror.org/05sj3n476","country_code":"JP","type":"education","lineage":["https://openalex.org/I161296585"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Katsuhiro Sekine","raw_affiliation_strings":["Department of Management Science, Tokyo University of Science, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Management Science, Tokyo University of Science, Tokyo, Japan","institution_ids":["https://openalex.org/I161296585"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089650488","display_name":"Tomoaki Tatsukawa","orcid":"https://orcid.org/0000-0002-0697-7897"},"institutions":[{"id":"https://openalex.org/I161296585","display_name":"Tokyo University of Science","ror":"https://ror.org/05sj3n476","country_code":"JP","type":"education","lineage":["https://openalex.org/I161296585"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tomoaki Tatsukawa","raw_affiliation_strings":["Department of Information and Computer Technology, Tokyo University of Science, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Information and Computer Technology, Tokyo University of Science, Tokyo, Japan","institution_ids":["https://openalex.org/I161296585"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5006325506"],"corresponding_institution_ids":["https://openalex.org/I161296585"],"apc_list":null,"apc_paid":null,"fwci":0.2019,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.57306545,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1196","last_page":"1203"},"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9979000091552734,"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9778000116348267,"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/crossover","display_name":"Crossover","score":0.9595835208892822},{"id":"https://openalex.org/keywords/evolutionary-algorithm","display_name":"Evolutionary algorithm","score":0.7652748823165894},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7182652950286865},{"id":"https://openalex.org/keywords/sorting","display_name":"Sorting","score":0.7047809958457947},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5815345048904419},{"id":"https://openalex.org/keywords/evolutionary-computation","display_name":"Evolutionary computation","score":0.5768702030181885},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.5450409650802612},{"id":"https://openalex.org/keywords/differential-evolution","display_name":"Differential evolution","score":0.5078609585762024},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4717840850353241},{"id":"https://openalex.org/keywords/multi-objective-optimization","display_name":"Multi-objective optimization","score":0.4711032509803772},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.4681307077407837},{"id":"https://openalex.org/keywords/operator","display_name":"Operator (biology)","score":0.4496328830718994},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4364597201347351},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.43612971901893616},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.4143570065498352},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4098402261734009},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.22123104333877563},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1485646665096283}],"concepts":[{"id":"https://openalex.org/C122507166","wikidata":"https://www.wikidata.org/wiki/Q628906","display_name":"Crossover","level":2,"score":0.9595835208892822},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.7652748823165894},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7182652950286865},{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.7047809958457947},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5815345048904419},{"id":"https://openalex.org/C105902424","wikidata":"https://www.wikidata.org/wiki/Q1197129","display_name":"Evolutionary computation","level":2,"score":0.5768702030181885},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.5450409650802612},{"id":"https://openalex.org/C74750220","wikidata":"https://www.wikidata.org/wiki/Q2662197","display_name":"Differential evolution","level":2,"score":0.5078609585762024},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4717840850353241},{"id":"https://openalex.org/C68781425","wikidata":"https://www.wikidata.org/wiki/Q2052203","display_name":"Multi-objective optimization","level":2,"score":0.4711032509803772},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.4681307077407837},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.4496328830718994},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4364597201347351},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.43612971901893616},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.4143570065498352},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4098402261734009},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.22123104333877563},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1485646665096283},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C86339819","wikidata":"https://www.wikidata.org/wiki/Q407384","display_name":"Transcription factor","level":3,"score":0.0},{"id":"https://openalex.org/C158448853","wikidata":"https://www.wikidata.org/wiki/Q425218","display_name":"Repressor","level":4,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssci.2018.8628707","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci.2018.8628707","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Symposium Series on Computational Intelligence (SSCI)","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/W47058917","https://openalex.org/W225560312","https://openalex.org/W1588375755","https://openalex.org/W1595159159","https://openalex.org/W1846834309","https://openalex.org/W1937286944","https://openalex.org/W1974276217","https://openalex.org/W2022485595","https://openalex.org/W2022897589","https://openalex.org/W2101104272","https://openalex.org/W2102625537","https://openalex.org/W2106334424","https://openalex.org/W2126105956","https://openalex.org/W2143185749","https://openalex.org/W2143381319","https://openalex.org/W2512027896","https://openalex.org/W2682627309","https://openalex.org/W2994964425","https://openalex.org/W4285719527","https://openalex.org/W6601885039","https://openalex.org/W6608886761","https://openalex.org/W6638887577","https://openalex.org/W6725722156"],"related_works":["https://openalex.org/W1988293173","https://openalex.org/W3177681191","https://openalex.org/W2076472895","https://openalex.org/W2389275641","https://openalex.org/W1606499289","https://openalex.org/W2895647686","https://openalex.org/W1985939653","https://openalex.org/W2039847237","https://openalex.org/W2015132550","https://openalex.org/W1966154590"],"abstract_inverted_index":{"The":[0,99,167],"performance":[1,77],"of":[2,64,101,177,218,249],"Multi-Objective":[3,158],"Evolutionary":[4,150,154,159],"Algorithms":[5],"(MOEAs)":[6],"depends":[7],"on":[8,48,76,170,181,228],"the":[9,30,42,62,74,80,175,178,186,197,207,229,247],"various":[10],"parameter":[11,32,44],"settings":[12],"such":[13,222],"as":[14,223],"population":[15],"size,":[16,18],"generation":[17],"crossover,":[19],"mutation":[20],"and":[21,52,83,95,107,130,157,191,210],"so":[22,202,244],"on.":[23],"It":[24],"is":[25,103,184],"often":[26],"difficult":[27],"to":[28,79,105,206,240],"know":[29],"appropriate":[31],"setting":[33],"for":[34,60],"a":[35,241],"real-world":[36],"optimization":[37,50],"problem":[38,51],"in":[39,67,71,164,188],"advance.":[40],"Besides,":[41],"optimal":[43],"values":[45],"might":[46],"depend":[47],"each":[49,182],"MOEA":[53,183],"itself.":[54],"However,":[55],"there":[56],"are":[57,85],"few":[58],"studies":[59],"investigating":[61],"effect":[63,176],"parameters":[65,217],"even":[66],"benchmark":[68,91,97,171],"problems.":[69,98],"Therefore,":[70],"this":[72,165],"study,":[73],"effects":[75],"due":[78],"crossover":[81,113,117,120,128,134,179,220,235],"operators":[82,221,236],"MOEAs":[84,209],"widely":[86],"investigated":[87],"by":[88],"using":[89],"eight":[90],"problems,":[92],"including":[93],"DTLZ":[94],"WFG":[96],"number":[100],"objectives":[102],"set":[104,239],"three":[106,190,213],"six.":[108],"We":[109],"consider":[110],"five":[111],"major":[112],"operators:":[114],"Simulated":[115],"Binary":[116],"(SBX),":[118],"Simplex":[119],"(SPX),":[121],"Differential":[122],"Evolution":[123],"operator":[124,180],"(DE),":[125],"Parent":[126],"Centric":[127],"(PCX),":[129],"Unimodal":[131],"Normal":[132],"Distribution":[133],"(UNDX).":[135],"As":[136],"MOEAs,":[137],"we":[138],"adopt":[139],"Non-dominated":[140,145],"sorting":[141,146],"genetic":[142,147],"algorithm-II":[143],"(NSGAII),":[144],"algorithm-III":[148],"(NSGA-III),-Dominance-based":[149],"Algorithm":[151,155,160],"(-MOEA),":[152],"Indicator-Based":[153],"(IBEA)":[156],"with":[161],"decomposition":[162],"(MOEA/D)":[163],"study.":[166],"experimental":[168],"results":[169],"problems":[172],"show":[173],"that":[174,196,233],"almost":[185],"same":[187],"both":[189],"six":[192],"objectives.":[193,214],"This":[194,231],"indicates":[195,232],"knowledge":[198],"has":[199],"been":[200],"obtained":[201],"far":[203,245],"could":[204],"adapt":[205],"other":[208],"more":[211],"than":[212],"In":[215],"addition,":[216],"some":[219],"SBX":[224],"have":[225],"little":[226],"impact":[227],"performance.":[230],"these":[234],"can":[237],"be":[238],"value":[242],"used":[243],"without":[246],"need":[248],"tuning.":[250]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
