{"id":"https://openalex.org/W4387006350","doi":"https://doi.org/10.1109/cec53210.2023.10254122","title":"Effects of Pareto Set on the Performance of Problem Reformulation-Based Large-Scale Multiobjective Optimization Algorithms","display_name":"Effects of Pareto Set on the Performance of Problem Reformulation-Based Large-Scale Multiobjective Optimization Algorithms","publication_year":2023,"publication_date":"2023-07-01","ids":{"openalex":"https://openalex.org/W4387006350","doi":"https://doi.org/10.1109/cec53210.2023.10254122"},"language":"en","primary_location":{"id":"doi:10.1109/cec53210.2023.10254122","doi":"https://doi.org/10.1109/cec53210.2023.10254122","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec53210.2023.10254122","pdf_url":null,"source":{"id":"https://openalex.org/S4363605353","display_name":"IEEE Congress on Evolutionary Computation (CEC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE Congress on Evolutionary Computation (CEC)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","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/A5041065952","display_name":"Haoran Gu","orcid":"https://orcid.org/0009-0008-8611-6464","observed_orcids":["https://orcid.org/0009-0008-8611-6464","https://orcid.org/0009-0005-1438-4994","https://orcid.org/0009-0007-0394-3708"]},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoran Gu","raw_affiliation_strings":["School of Artificial Intelligence Xidian University,Xi&#x0027;an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence Xidian University,Xi&#x0027;an,China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091324372","display_name":"Handing Wang","orcid":"https://orcid.org/0000-0002-4805-3780","observed_orcids":["https://orcid.org/0000-0002-4805-3780"]},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Handing Wang","raw_affiliation_strings":["School of Artificial Intelligence Xidian University,Xi&#x0027;an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence Xidian University,Xi&#x0027;an,China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032314861","display_name":"Yaochu Jin","orcid":"https://orcid.org/0000-0003-1100-0631","observed_orcids":["https://orcid.org/0000-0003-1100-0631"]},"institutions":[{"id":"https://openalex.org/I20121455","display_name":"Bielefeld University","ror":"https://ror.org/02hpadn98","country_code":"DE","type":"education","lineage":["https://openalex.org/I20121455"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Yaochu Jin","raw_affiliation_strings":["Bielefeld University,Faculty of Technology,Bielefeld,Germany","Faculty of Technology, Bielefeld University, Bielefeld, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bielefeld University,Faculty of Technology,Bielefeld,Germany","institution_ids":["https://openalex.org/I20121455"]},{"raw_affiliation_string":"Faculty of Technology, Bielefeld University, Bielefeld, Germany","institution_ids":["https://openalex.org/I20121455"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.9225,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.8601359,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9994999766349792,"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":0.9994999766349792,"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":0.00019999999494757503,"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":0.0,"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/large-scale-multi-objective-optimization","display_name":"large-scale multi-objective optimization","score":0.949999988079071},{"id":"https://openalex.org/keywords/problem-reformulation","display_name":"problem reformulation","score":0.8840000033378601},{"id":"https://openalex.org/keywords/pareto-set","display_name":"Pareto set","score":0.7839999794960022},{"id":"https://openalex.org/keywords/hypervolume","display_name":"hypervolume","score":0.8180000185966492},{"id":"https://openalex.org/keywords/evolutionary-algorithms","display_name":"evolutionary algorithms","score":0.6320000290870667},{"id":"https://openalex.org/keywords/test-suite-design","display_name":"test suite design","score":0.7170000076293945},{"id":"https://openalex.org/keywords/search-direction","display_name":"search direction","score":0.5040000081062317}],"concepts":[{"id":"https://openalex.org/C68781425","wikidata":"https://www.wikidata.org/wiki/Q2052203","display_name":"Multi-objective optimization","level":2,"score":0.7883323431015015},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.7288168668746948},{"id":"https://openalex.org/C137635306","wikidata":"https://www.wikidata.org/wiki/Q182667","display_name":"Pareto principle","level":2,"score":0.6674991250038147},{"id":"https://openalex.org/C151552104","wikidata":"https://www.wikidata.org/wiki/Q7705809","display_name":"Test suite","level":4,"score":0.6125856041908264},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5996062755584717},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.5650156140327454},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.5648822784423828},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5633713603019714},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5457671284675598},{"id":"https://openalex.org/C79581498","wikidata":"https://www.wikidata.org/wiki/Q1367530","display_name":"Suite","level":2,"score":0.4194263815879822},{"id":"https://openalex.org/C2986314615","wikidata":"https://www.wikidata.org/wiki/Q36829","display_name":"Pareto optimal","level":3,"score":0.418820858001709},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38296908140182495},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37870723009109497},{"id":"https://openalex.org/C128942645","wikidata":"https://www.wikidata.org/wiki/Q1568346","display_name":"Test case","level":3,"score":0.23172372579574585},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.08295893669128418},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cec53210.2023.10254122","doi":"https://doi.org/10.1109/cec53210.2023.10254122","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec53210.2023.10254122","pdf_url":null,"source":{"id":"https://openalex.org/S4363605353","display_name":"IEEE Congress on Evolutionary Computation (CEC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE Congress on Evolutionary Computation (CEC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G5380021153","display_name":null,"funder_award_id":"61976165","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W350155834","https://openalex.org/W1544309315","https://openalex.org/W1555689267","https://openalex.org/W1595159159","https://openalex.org/W1833634424","https://openalex.org/W1971537182","https://openalex.org/W2096166399","https://openalex.org/W2117502083","https://openalex.org/W2126105956","https://openalex.org/W2130166265","https://openalex.org/W2140886193","https://openalex.org/W2146446525","https://openalex.org/W2153654820","https://openalex.org/W2155005783","https://openalex.org/W2329749247","https://openalex.org/W2461645024","https://openalex.org/W2510493362","https://openalex.org/W2513211214","https://openalex.org/W2558118859","https://openalex.org/W2616257225","https://openalex.org/W2733889422","https://openalex.org/W2758271972","https://openalex.org/W2764251381","https://openalex.org/W2772724326","https://openalex.org/W2914542742","https://openalex.org/W2932748297","https://openalex.org/W2946739419","https://openalex.org/W3041654307","https://openalex.org/W3134440233","https://openalex.org/W4312501469","https://openalex.org/W4313009019"],"related_works":["https://openalex.org/W4401415131","https://openalex.org/W2914542742","https://openalex.org/W7138874107","https://openalex.org/W4399686948","https://openalex.org/W4396888627","https://openalex.org/W4387027538","https://openalex.org/W3193117796","https://openalex.org/W4394939073","https://openalex.org/W4411600988","https://openalex.org/W7133313450"],"abstract_inverted_index":{"Recently,":[0],"a":[1,40,59,170],"number":[2],"of":[3,42,106,110,122,150,183],"evolutionary":[4],"algorithms":[5],"(EAs)":[6],"have":[7],"been":[8],"proposed":[9,87],"for":[10,90,158],"large-scale":[11,24,53,91],"multiobjective":[12,25,54,92],"optimization.":[13],"Among":[14],"them,":[15],"due":[16],"to":[17,31,102,114,146],"the":[18,21,36,51,66,69,74,78,82,94,103,120,131,139,147,153,164,181,189,192],"high":[19],"efficiency,":[20],"problem":[22,56,63],"reformulation-based":[23],"optimization":[26,55,62],"framework":[27],"(LSMOF)":[28],"has":[29],"shown":[30],"be":[32],"promising.":[33],"By":[34],"associating":[35],"weight":[37,70],"variables":[38,71],"with":[39,191],"set":[41,166],"specific":[43],"bi-directional":[44,104,123,140],"vectors":[45,105,124,141],"representing":[46],"search":[47,96],"directions,":[48],"LSMOF":[49,151,161,184],"reformulates":[50],"original":[52],"(LSMOP)":[57],"into":[58],"low-dimensional":[60],"single-objective":[61],"(SOP).":[64],"For":[65],"reformulated":[67],"SOP,":[68],"are":[72,98,142,144],"as":[73,81],"decision":[75],"vector":[76],"and":[77,133],"hypervolume":[79],"is":[80,113,168,174],"objective.":[83],"In":[84],"many":[85],"recently":[86],"competitive":[88],"EAs":[89],"optimization,":[93],"promising":[95],"directions":[97],"also":[99],"specified":[100],"similar":[101],"LSMOF.":[107,126],"The":[108,176],"aim":[109],"this":[111],"paper":[112],"point":[115],"out":[116],"some":[117],"challenges":[118],"in":[119,125],"construction":[121],"We":[127],"first":[128],"verify":[129],"that":[130,180],"lower":[132],"upper":[134],"boundary":[135],"points":[136],"from":[137],"which":[138],"generated":[143],"crucial":[145],"good":[148],"performance":[149,182],"on":[152,188],"LSMOP":[154],"test":[155,172],"suite.":[156],"Then,":[157],"demonstrating":[159],"how":[160],"performs":[162],"when":[163],"Pareto":[165],"(PS)":[167],"changed,":[169],"new":[171,193],"suite":[173],"designed.":[175],"experimental":[177],"results":[178],"show":[179],"will":[185],"deteriorate":[186],"rapidly":[187],"problems":[190],"PS.":[194]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2023-09-26T00:00:00"}
