{"id":"https://openalex.org/W4285734629","doi":"https://doi.org/10.1145/3512290.3528732","title":"An improved Pareto front modeling algorithm for large-scale many-objective optimization","display_name":"An improved Pareto front modeling algorithm for large-scale many-objective optimization","publication_year":2022,"publication_date":"2022-07-08","ids":{"openalex":"https://openalex.org/W4285734629","doi":"https://doi.org/10.1145/3512290.3528732"},"language":"en","primary_location":{"id":"doi:10.1145/3512290.3528732","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3512290.3528732","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3512290.3528732","source":{"id":"https://openalex.org/S4363608932","display_name":"Proceedings of the Genetic and Evolutionary Computation Conference","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Genetic and Evolutionary Computation Conference","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3512290.3528732","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067127346","display_name":"Annibale Panichella","orcid":"https://orcid.org/0000-0002-7395-3588"},"institutions":[{"id":"https://openalex.org/I98358874","display_name":"Delft University of Technology","ror":"https://ror.org/02e2c7k09","country_code":"NL","type":"education","lineage":["https://openalex.org/I98358874"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Annibale Panichella","raw_affiliation_strings":["Delft University of Technology, Delft, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Delft University of Technology, Delft, The Netherlands","institution_ids":["https://openalex.org/I98358874"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5067127346"],"corresponding_institution_ids":["https://openalex.org/I98358874"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":98,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"565","last_page":"573"},"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/T11115","display_name":"Topology Optimization in Engineering","score":0.9902999997138977,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9901000261306763,"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/convergence","display_name":"Convergence (economics)","score":0.6903283596038818},{"id":"https://openalex.org/keywords/evolutionary-algorithm","display_name":"Evolutionary algorithm","score":0.650344967842102},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.6324506402015686},{"id":"https://openalex.org/keywords/multi-objective-optimization","display_name":"Multi-objective optimization","score":0.6224312782287598},{"id":"https://openalex.org/keywords/geodesic","display_name":"Geodesic","score":0.6010150909423828},{"id":"https://openalex.org/keywords/curvature","display_name":"Curvature","score":0.562341034412384},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5056564807891846},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4926477074623108},{"id":"https://openalex.org/keywords/evolutionary-computation","display_name":"Evolutionary computation","score":0.48817116022109985},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.447086364030838},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.42299896478652954},{"id":"https://openalex.org/keywords/pareto-principle","display_name":"Pareto principle","score":0.41492757201194763},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.18637615442276}],"concepts":[{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6903283596038818},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.650344967842102},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6324506402015686},{"id":"https://openalex.org/C68781425","wikidata":"https://www.wikidata.org/wiki/Q2052203","display_name":"Multi-objective optimization","level":2,"score":0.6224312782287598},{"id":"https://openalex.org/C165818556","wikidata":"https://www.wikidata.org/wiki/Q213488","display_name":"Geodesic","level":2,"score":0.6010150909423828},{"id":"https://openalex.org/C195065555","wikidata":"https://www.wikidata.org/wiki/Q214881","display_name":"Curvature","level":2,"score":0.562341034412384},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5056564807891846},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4926477074623108},{"id":"https://openalex.org/C105902424","wikidata":"https://www.wikidata.org/wiki/Q1197129","display_name":"Evolutionary computation","level":2,"score":0.48817116022109985},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.447086364030838},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.42299896478652954},{"id":"https://openalex.org/C137635306","wikidata":"https://www.wikidata.org/wiki/Q182667","display_name":"Pareto principle","level":2,"score":0.41492757201194763},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.18637615442276},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3512290.3528732","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3512290.3528732","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3512290.3528732","source":{"id":"https://openalex.org/S4363608932","display_name":"Proceedings of the Genetic and Evolutionary Computation Conference","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Genetic and Evolutionary Computation Conference","raw_type":"proceedings-article"},{"id":"pmh:oai:tudelft.nl:uuid:fe5a68d7-1291-46a1-9ac8-47b6a05b8537","is_oa":false,"landing_page_url":"http://resolver.tudelft.nl/uuid:fe5a68d7-1291-46a1-9ac8-47b6a05b8537","pdf_url":null,"source":{"id":"https://openalex.org/S4306400906","display_name":"Research Repository (Delft University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I98358874","host_organization_name":"Delft University of Technology","host_organization_lineage":["https://openalex.org/I98358874"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"conference paper"},{"id":"pmh:oai:zenodo.org:6462859","is_oa":true,"landing_page_url":"https://zenodo.org/record/6462859","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"software"}],"best_oa_location":{"id":"doi:10.1145/3512290.3528732","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3512290.3528732","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3512290.3528732","source":{"id":"https://openalex.org/S4363608932","display_name":"Proceedings of the Genetic and Evolutionary Computation Conference","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Genetic and Evolutionary Computation Conference","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","score":0.6399999856948853,"display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4285734629.pdf","grobid_xml":"https://content.openalex.org/works/W4285734629.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W224959492","https://openalex.org/W244947329","https://openalex.org/W1588375755","https://openalex.org/W1595498733","https://openalex.org/W1599808047","https://openalex.org/W2010398592","https://openalex.org/W2022485595","https://openalex.org/W2024008934","https://openalex.org/W2085507535","https://openalex.org/W2126105956","https://openalex.org/W2135974394","https://openalex.org/W2143185749","https://openalex.org/W2143381319","https://openalex.org/W2203770136","https://openalex.org/W2276739600","https://openalex.org/W2327830569","https://openalex.org/W2510493362","https://openalex.org/W2599937626","https://openalex.org/W2733459154","https://openalex.org/W2764251381","https://openalex.org/W2896405912","https://openalex.org/W2906115061","https://openalex.org/W2913670039","https://openalex.org/W2946739419","https://openalex.org/W2953831633","https://openalex.org/W2963185242","https://openalex.org/W3046910774","https://openalex.org/W3081699271","https://openalex.org/W3203295779","https://openalex.org/W4210695517","https://openalex.org/W4233913520","https://openalex.org/W4285662678","https://openalex.org/W4286532188","https://openalex.org/W4286822879","https://openalex.org/W4302367531"],"related_works":["https://openalex.org/W2090178682","https://openalex.org/W2001591765","https://openalex.org/W4241467429","https://openalex.org/W4297582752","https://openalex.org/W4285805405","https://openalex.org/W2906115061","https://openalex.org/W2977596624","https://openalex.org/W2073147994","https://openalex.org/W85101999","https://openalex.org/W2145877535"],"abstract_inverted_index":{"A":[0],"key":[1],"idea":[2],"in":[3],"many-objective":[4,168],"optimization":[5],"is":[6],"to":[7,27,71,78],"approximate":[8],"the":[9,28,47,52,65,68,79,93,103,118,133,151],"optimal":[10,29],"Pareto":[11,53],"front":[12,30,70,90],"using":[13,92,112],"a":[14,85],"set":[15,23],"of":[16,51,67,109,117],"representative":[17],"non-dominated":[18,69,89,110],"solutions.":[19],"The":[20],"produced":[21],"solution":[22],"should":[24],"be":[25],"close":[26],"(convergence)":[31],"and":[32,43,153,174],"well-diversified":[33],"(diversity).":[34],"Recent":[35],"studies":[36],"have":[37,59,127],"shown":[38],"that":[39,63,76,157],"measuring":[40],"both":[41],"convergence":[42],"diversity":[44],"depends":[45],"on":[46,120],"shape":[48,66],"(or":[49],"curvature)":[50],"front.":[54],"In":[55],"recent":[56],"years,":[57],"researchers":[58],"proposed":[60],"evolutionary":[61,130],"algorithms":[62],"model":[64],"define":[72],"environmental":[73],"selection":[74],"strategies":[75],"adapt":[77],"underlying":[80],"geometry.":[81],"This":[82],"paper":[83],"proposes":[84],"novel":[86],"method":[87,96],"for":[88,97],"modeling":[91],"Newton-Raphson":[94],"iterative":[95],"roots":[98],"finding.":[99],"Second,":[100],"we":[101,142],"compute":[102],"distance":[104,119],"(diversity)":[105],"between":[106],"each":[107],"pair":[108],"solutions":[111],"geodesics,":[113],"which":[114,141],"are":[115],"generalizations":[116],"Riemann":[121],"manifolds":[122],"(curved":[123],"topological":[124],"spaces).":[125],"We":[126],"introduced":[128],"an":[129],"algorithm":[131],"within":[132],"Adaptive":[134],"Geometry":[135],"Estimation":[136],"based":[137],"MOEA":[138],"(AGE-MOEA)":[139],"framework,":[140],"called":[143],"AGE-MOEA-II.":[144],"Computational":[145],"experiments":[146],"with":[147],"17":[148],"problems":[149],"from":[150],"WFG":[152],"SMOP":[154],"benchmarks":[155],"show":[156],"AGE-MOEA-II":[158],"outperforms":[159],"its":[160],"predecessor":[161],"AGE-MOEA":[162],"as":[163,165],"well":[164],"other":[166],"state-of-the-art":[167],"algorithms,":[169],"i.e.,":[170],"NSGA-III,":[171],"MOEA/D,":[172],"VaEA,":[173],"LMEA.":[175]},"counts_by_year":[{"year":2026,"cited_by_count":17},{"year":2025,"cited_by_count":39},{"year":2024,"cited_by_count":31},{"year":2023,"cited_by_count":11}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
