{"id":"https://openalex.org/W2939235155","doi":"https://doi.org/10.1145/3321707.3321834","title":"Runtime analysis of the univariate marginal distribution algorithm under low selective pressure and prior noise","display_name":"Runtime analysis of the univariate marginal distribution algorithm under low selective pressure and prior noise","publication_year":2019,"publication_date":"2019-07-03","ids":{"openalex":"https://openalex.org/W2939235155","doi":"https://doi.org/10.1145/3321707.3321834","mag":"2939235155"},"language":"en","primary_location":{"id":"doi:10.1145/3321707.3321834","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3321707.3321834","pdf_url":null,"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":null,"license_id":null,"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":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1904.09239","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026427521","display_name":"Per Kristian Lehre","orcid":"https://orcid.org/0000-0002-9521-1251"},"institutions":[{"id":"https://openalex.org/I79619799","display_name":"University of Birmingham","ror":"https://ror.org/03angcq70","country_code":"GB","type":"education","lineage":["https://openalex.org/I79619799"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Per Kristian Lehre","raw_affiliation_strings":["University of Birmingham, Birmingham, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Birmingham, Birmingham, United Kingdom","institution_ids":["https://openalex.org/I79619799"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012413932","display_name":"Phan Trung Hai Nguyen","orcid":"https://orcid.org/0000-0003-0783-2224"},"institutions":[{"id":"https://openalex.org/I79619799","display_name":"University of Birmingham","ror":"https://ror.org/03angcq70","country_code":"GB","type":"education","lineage":["https://openalex.org/I79619799"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Phan Trung Hai Nguyen","raw_affiliation_strings":["University of Birmingham, Birmingham, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Birmingham, Birmingham, United Kingdom","institution_ids":["https://openalex.org/I79619799"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I79619799"],"apc_list":null,"apc_paid":null,"fwci":1.0975,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.83094063,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1497","last_page":"1505"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9952999949455261,"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"}},"topics":[{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9952999949455261,"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":0.9948999881744385,"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/T11269","display_name":"Algorithms and Data Compression","score":0.9939000010490417,"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/univariate","display_name":"Univariate","score":0.7031968832015991},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.651544988155365},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6287062168121338},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5676524639129639},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5519027709960938},{"id":"https://openalex.org/keywords/marginal-distribution","display_name":"Marginal distribution","score":0.5509740114212036},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5488666296005249},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.5016634464263916},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4738260507583618},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.42512246966362},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35013705492019653},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3243342638015747},{"id":"https://openalex.org/keywords/random-variable","display_name":"Random variable","score":0.26890861988067627},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.17020070552825928},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.12408548593521118},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.10111075639724731}],"concepts":[{"id":"https://openalex.org/C199163554","wikidata":"https://www.wikidata.org/wiki/Q1681619","display_name":"Univariate","level":3,"score":0.7031968832015991},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.651544988155365},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6287062168121338},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5676524639129639},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5519027709960938},{"id":"https://openalex.org/C165216359","wikidata":"https://www.wikidata.org/wiki/Q670653","display_name":"Marginal distribution","level":3,"score":0.5509740114212036},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5488666296005249},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5016634464263916},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4738260507583618},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.42512246966362},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35013705492019653},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3243342638015747},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.26890861988067627},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.17020070552825928},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.12408548593521118},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.10111075639724731},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1145/3321707.3321834","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3321707.3321834","pdf_url":null,"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":null,"license_id":null,"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:arXiv.org:1904.09239","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1904.09239","pdf_url":"https://arxiv.org/pdf/1904.09239","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:pure.atira.dk:Publications/3769bca6-3f18-425a-bc63-bcaeca5a55e6","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306402634","display_name":"University of Birmingham Research Portal (University of Birmingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79619799","host_organization_name":"University of Birmingham","host_organization_lineage":["https://openalex.org/I79619799"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""},{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/3769bca6-3f18-425a-bc63-bcaeca5a55e6","is_oa":true,"landing_page_url":"https://research.birmingham.ac.uk/en/publications/3769bca6-3f18-425a-bc63-bcaeca5a55e6","pdf_url":null,"source":{"id":"https://openalex.org/S4306402634","display_name":"University of Birmingham Research Portal (University of Birmingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79619799","host_organization_name":"University of Birmingham","host_organization_lineage":["https://openalex.org/I79619799"],"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":null,"raw_type":"contributionToPeriodical"},{"id":"pmh:oai:pure.atira.dk:publications/3769bca6-3f18-425a-bc63-bcaeca5a55e6","is_oa":false,"landing_page_url":"http://www.scopus.com/inward/record.url?scp=85072343106&partnerID=8YFLogxK","pdf_url":null,"source":{"id":"https://openalex.org/S4306402634","display_name":"University of Birmingham Research Portal (University of Birmingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79619799","host_organization_name":"University of Birmingham","host_organization_lineage":["https://openalex.org/I79619799"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1904.09239","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1904.09239","pdf_url":"https://arxiv.org/pdf/1904.09239","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.7799999713897705}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W139482607","https://openalex.org/W1170402926","https://openalex.org/W1479911746","https://openalex.org/W1512383952","https://openalex.org/W1540706608","https://openalex.org/W1692958259","https://openalex.org/W1801849579","https://openalex.org/W1975682709","https://openalex.org/W1989244967","https://openalex.org/W1989274820","https://openalex.org/W1990799344","https://openalex.org/W1991354823","https://openalex.org/W1993965167","https://openalex.org/W1999803056","https://openalex.org/W2003289346","https://openalex.org/W2004578565","https://openalex.org/W2048498390","https://openalex.org/W2050215344","https://openalex.org/W2091239497","https://openalex.org/W2099934773","https://openalex.org/W2128151276","https://openalex.org/W2165220807","https://openalex.org/W2290719151","https://openalex.org/W2499149626","https://openalex.org/W2501406586","https://openalex.org/W2527291902","https://openalex.org/W2589005638","https://openalex.org/W2605136245","https://openalex.org/W2724311120","https://openalex.org/W2727744916","https://openalex.org/W2751862591","https://openalex.org/W2804953719","https://openalex.org/W2806837893","https://openalex.org/W2807845952","https://openalex.org/W2875338278","https://openalex.org/W2883312863","https://openalex.org/W2885751302","https://openalex.org/W2887735318","https://openalex.org/W2963262140","https://openalex.org/W3099820049","https://openalex.org/W3154803405","https://openalex.org/W4212805448"],"related_works":["https://openalex.org/W1828158523","https://openalex.org/W2047547195","https://openalex.org/W2378211422","https://openalex.org/W204175656","https://openalex.org/W2911841387","https://openalex.org/W2803255289","https://openalex.org/W1512294453","https://openalex.org/W1993992974","https://openalex.org/W2085244387","https://openalex.org/W2352581933"],"abstract_inverted_index":{"We":[0],"perform":[1],"a":[2,16,28,35,64,89,107,130],"rigorous":[3,160],"runtime":[4,50,91,139],"analysis":[5],"for":[6,119,140],"the":[7,13,21,41,48,71,86,99,114,120,124,127,141,146,168,171],"Univariate":[8],"Marginal":[9],"Distribution":[10],"Algorithm":[11],"on":[12,47,113,126],"LeadingOnes":[14],"function,":[15],"well-known":[17],"benchmark":[18],"function":[19,128],"in":[20,96],"theory":[22],"community":[23],"of":[24,38,110,170],"evolutionary":[25],"computation":[26],"with":[27,74,92,159],"high":[29,93],"correlation":[30],"between":[31],"decision":[32],"variables.":[33],"For":[34],"problem":[36],"instance":[37],"size":[39],"n,":[40],"currently":[42],"best":[43],"known":[44],"upper":[45],"bound":[46,66,109],"expected":[49,115,138],"is":[51,77,102],"O":[52],"(n\u03bb":[53],"log":[54],"\u03bb":[55],"+":[56],"n2)":[57],"(Dang":[58],"and":[59,95,134],"Lehre,":[60],"GECCO":[61],"2015),":[62],"while":[63],"lower":[65,108],"necessary":[67],"to":[68],"understand":[69],"how":[70],"algorithm":[72,87,125],"copes":[73],"variable":[75],"dependencies":[76],"still":[78],"missing.":[79],"Motivated":[80],"by":[81,153],"this,":[82],"we":[83,105,118],"show":[84],"that":[85],"requires":[88],"e\u03a9(\u00b5)":[90],"probability":[94],"expectation":[97],"if":[98],"selective":[100],"pressure":[101],"low;":[103],"otherwise,":[104],"obtain":[106,135],"[MATH":[111],"HERE]":[112],"runtime.":[116],"Furthermore,":[117],"first":[121],"time":[122],"consider":[123],"under":[129],"prior":[131],"noise":[132],"model":[133],"an":[136],"O(n2)":[137],"optimal":[142],"parameter":[143],"settings.":[144],"In":[145],"end,":[147],"our":[148],"theoretical":[149],"results":[150],"are":[151],"accompanied":[152],"empirical":[154],"findings,":[155],"not":[156],"only":[157],"matching":[158],"analyses":[161],"but":[162],"also":[163],"providing":[164],"new":[165],"insights":[166],"into":[167],"behaviour":[169],"algorithm.":[172]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2020-11-23T00:00:00"}
