{"id":"https://openalex.org/W2098120219","doi":"https://doi.org/10.1145/1830483.1830575","title":"DBSCAN-based multi-objective niching to approximate equivalent pareto-subsets","display_name":"DBSCAN-based multi-objective niching to approximate equivalent pareto-subsets","publication_year":2010,"publication_date":"2010-07-07","ids":{"openalex":"https://openalex.org/W2098120219","doi":"https://doi.org/10.1145/1830483.1830575","mag":"2098120219"},"language":"en","primary_location":{"id":"doi:10.1145/1830483.1830575","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1830483.1830575","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th annual conference on Genetic and evolutionary computation","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/A5103020462","display_name":"Oliver Kr\u00e4mer","orcid":"https://orcid.org/0000-0001-7607-1700"},"institutions":[{"id":"https://openalex.org/I1297971548","display_name":"International Computer Science Institute","ror":"https://ror.org/01ewh7m12","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1297971548"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Oliver Kramer","raw_affiliation_strings":["International Computer Science Institute Berkeley, Berkeley, CA, USA"],"affiliations":[{"raw_affiliation_string":"International Computer Science Institute Berkeley, Berkeley, CA, USA","institution_ids":["https://openalex.org/I1297971548"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074017762","display_name":"Holger Danielsiek","orcid":null},"institutions":[{"id":"https://openalex.org/I200332995","display_name":"TU Dortmund University","ror":"https://ror.org/01k97gp34","country_code":"DE","type":"education","lineage":["https://openalex.org/I200332995"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Holger Danielsiek","raw_affiliation_strings":["Technische Universit\u00e4t Dortmund, Dortmund, Germany"],"affiliations":[{"raw_affiliation_string":"Technische Universit\u00e4t Dortmund, Dortmund, Germany","institution_ids":["https://openalex.org/I200332995"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5103020462"],"corresponding_institution_ids":["https://openalex.org/I1297971548"],"apc_list":null,"apc_paid":null,"fwci":1.3381,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.81365642,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"503","last_page":"510"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":1.0,"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":1.0,"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":0.9965000152587891,"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/T11053","display_name":"Process Optimization and Integration","score":0.9908999800682068,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7209741473197937},{"id":"https://openalex.org/keywords/dbscan","display_name":"DBSCAN","score":0.6051677465438843},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.58409184217453},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5714260935783386},{"id":"https://openalex.org/keywords/pareto-principle","display_name":"Pareto principle","score":0.5684492588043213},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5119863152503967},{"id":"https://openalex.org/keywords/multi-objective-optimization","display_name":"Multi-objective optimization","score":0.4832914173603058},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4595256447792053},{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.4277169704437256},{"id":"https://openalex.org/keywords/parameterized-complexity","display_name":"Parameterized complexity","score":0.41930750012397766},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.41196054220199585},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2930361032485962},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.25625213980674744},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2084231674671173},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.11979374289512634},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0735166072845459},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.07308679819107056}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7209741473197937},{"id":"https://openalex.org/C46576248","wikidata":"https://www.wikidata.org/wiki/Q1114630","display_name":"DBSCAN","level":5,"score":0.6051677465438843},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.58409184217453},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5714260935783386},{"id":"https://openalex.org/C137635306","wikidata":"https://www.wikidata.org/wiki/Q182667","display_name":"Pareto principle","level":2,"score":0.5684492588043213},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5119863152503967},{"id":"https://openalex.org/C68781425","wikidata":"https://www.wikidata.org/wiki/Q2052203","display_name":"Multi-objective optimization","level":2,"score":0.4832914173603058},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4595256447792053},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.4277169704437256},{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.41930750012397766},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.41196054220199585},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2930361032485962},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25625213980674744},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2084231674671173},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.11979374289512634},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0735166072845459},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.07308679819107056},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","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/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1830483.1830575","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1830483.1830575","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th annual conference on Genetic and evolutionary computation","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5199999809265137,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W42649658","https://openalex.org/W1553373771","https://openalex.org/W1576660662","https://openalex.org/W1582055249","https://openalex.org/W1606852530","https://openalex.org/W1612556207","https://openalex.org/W1639032689","https://openalex.org/W1673310716","https://openalex.org/W1905847227","https://openalex.org/W2038420231","https://openalex.org/W2106334424","https://openalex.org/W2116661285","https://openalex.org/W2117411467","https://openalex.org/W2126105956","https://openalex.org/W2126926002","https://openalex.org/W2144481507","https://openalex.org/W2152150600","https://openalex.org/W2158320871","https://openalex.org/W2994964425","https://openalex.org/W3023540311","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2090178682","https://openalex.org/W2073147994","https://openalex.org/W2001591765","https://openalex.org/W4241467429","https://openalex.org/W2384474142","https://openalex.org/W3083133203","https://openalex.org/W2744462909","https://openalex.org/W1971520370","https://openalex.org/W1588199609","https://openalex.org/W1550055091"],"abstract_inverted_index":{"In":[0,32],"systems":[1],"optimization":[2,103],"and":[3,49,121],"machine":[4],"learning":[5],"multiple":[6],"alternative":[7],"solutions":[8,43],"may":[9,29],"exist":[10],"in":[11,47,54,71,76],"different":[12],"parts":[13,20],"of":[14,21,26,118,128,145],"decision":[15,50,77],"space":[16,56,78],"for":[17,114],"the":[18,22,66,86,96,101,115,126,143,146],"same":[19],"Pareto-front.":[23],"The":[24,92,132],"detection":[25],"equivalent":[27],"Pareto-subsets":[28],"be":[30],"desirable.":[31],"this":[33],"paper":[34],"we":[35,57,79],"introduce":[36,80,111],"a":[37,61,81],"niching":[38,82,133],"method":[39,63,90,134],"that":[40,84],"approximates":[41],"Pareto-optimal":[42],"with":[44,142],"diversity":[45,53,75],"mechanisms":[46],"objective":[48,55,72],"space.":[51,73],"For":[52,74],"use":[58],"rake":[59,123],"selection,":[60],"selection":[62,124],"based":[64,88],"on":[65,106,138],"distances":[67],"to":[68,98],"reference":[69],"lines":[70],"approach":[83],"uses":[85],"density":[87],"clustering":[89,93,119],"DBSCAN.":[91],"process":[94,104],"assigns":[95],"population":[97],"niches":[99],"while":[100],"multi-objective":[102],"concentrates":[105],"each":[107],"niche":[108],"independently.":[109],"We":[110],"an":[112],"indicator":[113],"adaptive":[116,129],"control":[117],"processes,":[120],"extend":[122],"by":[125],"concept":[127],"corner":[130],"points.":[131],"is":[135],"experimentally":[136],"validated":[137],"parameterized":[139],"test":[140],"function":[141],"help":[144],"S-metric.":[147]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2016,"cited_by_count":2},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
