{"id":"https://openalex.org/W4385211453","doi":"https://doi.org/10.1145/3583133.3596403","title":"Configuring a Hierarchical Evolutionary Strategy Using Exploratory Landscape Analysis","display_name":"Configuring a Hierarchical Evolutionary Strategy Using Exploratory Landscape Analysis","publication_year":2023,"publication_date":"2023-07-15","ids":{"openalex":"https://openalex.org/W4385211453","doi":"https://doi.org/10.1145/3583133.3596403"},"language":"en","primary_location":{"id":"doi:10.1145/3583133.3596403","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3583133.3596403","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Companion 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/A5029673696","display_name":"Hubert Guzowski","orcid":"https://orcid.org/0000-0002-9678-0384"},"institutions":[{"id":"https://openalex.org/I686019","display_name":"AGH University of Krakow","ror":"https://ror.org/00bas1c41","country_code":"PL","type":"education","lineage":["https://openalex.org/I686019"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Hubert Guzowski","raw_affiliation_strings":["AGH University of Science and Technology, Krak\u00f3w, Poland"],"affiliations":[{"raw_affiliation_string":"AGH University of Science and Technology, Krak\u00f3w, Poland","institution_ids":["https://openalex.org/I686019"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027877891","display_name":"Maciej Sm\u00f3\u0142ka","orcid":"https://orcid.org/0000-0002-3386-0555"},"institutions":[{"id":"https://openalex.org/I686019","display_name":"AGH University of Krakow","ror":"https://ror.org/00bas1c41","country_code":"PL","type":"education","lineage":["https://openalex.org/I686019"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Maciej Smo\u0142ka","raw_affiliation_strings":["AGH University of Science and Technology, Krak\u00f3w, Poland"],"affiliations":[{"raw_affiliation_string":"AGH University of Science and Technology, Krak\u00f3w, Poland","institution_ids":["https://openalex.org/I686019"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5029673696"],"corresponding_institution_ids":["https://openalex.org/I686019"],"apc_list":null,"apc_paid":null,"fwci":0.8068,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.7591392,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1785","last_page":"1792"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9995999932289124,"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":0.9995999932289124,"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":0.993399977684021,"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":0.9843000173568726,"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/computer-science","display_name":"Computer science","score":0.7576432824134827},{"id":"https://openalex.org/keywords/evolutionary-algorithm","display_name":"Evolutionary algorithm","score":0.5840603709220886},{"id":"https://openalex.org/keywords/fitness-landscape","display_name":"Fitness landscape","score":0.56833815574646},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5264478325843811},{"id":"https://openalex.org/keywords/hierarchy","display_name":"Hierarchy","score":0.4805639088153839},{"id":"https://openalex.org/keywords/suite","display_name":"Suite","score":0.44939640164375305},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.402737557888031},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39134690165519714},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3479135036468506},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.32376939058303833},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11168035864830017},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.09889009594917297}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7576432824134827},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.5840603709220886},{"id":"https://openalex.org/C91852762","wikidata":"https://www.wikidata.org/wiki/Q3307742","display_name":"Fitness landscape","level":3,"score":0.56833815574646},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5264478325843811},{"id":"https://openalex.org/C31170391","wikidata":"https://www.wikidata.org/wiki/Q188619","display_name":"Hierarchy","level":2,"score":0.4805639088153839},{"id":"https://openalex.org/C79581498","wikidata":"https://www.wikidata.org/wiki/Q1367530","display_name":"Suite","level":2,"score":0.44939640164375305},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.402737557888031},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39134690165519714},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3479135036468506},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.32376939058303833},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11168035864830017},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.09889009594917297},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C34447519","wikidata":"https://www.wikidata.org/wiki/Q179522","display_name":"Market economy","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3583133.3596403","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3583133.3596403","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Companion Conference on Genetic and Evolutionary Computation","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","score":0.47999998927116394,"id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1495775210","https://openalex.org/W1977945115","https://openalex.org/W1997807546","https://openalex.org/W2002731955","https://openalex.org/W2006565216","https://openalex.org/W2042253843","https://openalex.org/W2063966510","https://openalex.org/W2089213632","https://openalex.org/W2095314857","https://openalex.org/W2112449769","https://openalex.org/W2143192733","https://openalex.org/W2150337126","https://openalex.org/W2151554678","https://openalex.org/W2294293646","https://openalex.org/W2483278326","https://openalex.org/W2506038236","https://openalex.org/W2558097110","https://openalex.org/W2588144518","https://openalex.org/W2750236386","https://openalex.org/W2768617563","https://openalex.org/W2786564723","https://openalex.org/W2790634817","https://openalex.org/W2795799780","https://openalex.org/W2870843528","https://openalex.org/W2891971415","https://openalex.org/W2936279393","https://openalex.org/W2946586661","https://openalex.org/W3041403246","https://openalex.org/W3131309474","https://openalex.org/W3199199693","https://openalex.org/W4285152728","https://openalex.org/W4286970057","https://openalex.org/W4306968532","https://openalex.org/W4403360948","https://openalex.org/W6894201702"],"related_works":["https://openalex.org/W4231704780","https://openalex.org/W2083794993","https://openalex.org/W352609212","https://openalex.org/W4200340037","https://openalex.org/W1511772879","https://openalex.org/W4379115841","https://openalex.org/W608917066","https://openalex.org/W4283652261","https://openalex.org/W585424826","https://openalex.org/W564602992"],"abstract_inverted_index":{"Hierarchic":[0],"Memetic":[1],"Strategy":[2],"(HMS)":[3],"is":[4],"a":[5,24,49,60,80,105,124],"stochastic":[6],"global":[7],"optimizer":[8],"designed":[9],"to":[10,119],"tackle":[11],"highly":[12],"multimodal":[13],"problems.":[14],"It":[15],"consists":[16],"of":[17,38,62,75,82,89,95,101,107,116,123,133,150],"parallel":[18],"running":[19],"optimization":[20,91],"methods":[21,67,118],"organized":[22],"in":[23],"tree":[25],"hierarchy.":[26],"Depending":[27],"on":[28,36,56,86],"the":[29,39,73,87,99,121,141],"task,":[30],"different":[31,148],"algorithms":[32,85,112],"can":[33],"be":[34],"utilized":[35],"each":[37],"levels.":[40],"In":[41],"this":[42,96],"paper,":[43],"we":[44],"incorporate":[45],"into":[46,140],"HMS's":[47],"structure":[48],"mechanism":[50],"for":[51,111,147],"choosing":[52],"its":[53],"configuration":[54,122],"based":[55],"information":[57],"gathered":[58],"by":[59],"set":[61,106],"Exploratory":[63],"Landscape":[64],"Analysis":[65],"(ELA)":[66],"and":[68,103,137,145],"hyperparametric":[69],"optimization.":[70],"We":[71],"compared":[72],"performance":[74],"such":[76],"configured":[77],"HMS":[78,102],"with":[79],"portfolio":[81],"proven":[83],"state-of-the-art":[84],"suite":[88],"black-box":[90],"functions.":[92,152],"The":[93,114],"results":[94],"work":[97],"show":[98],"efficacy":[100],"provide":[104],"default":[108],"parameters":[109],"evaluated":[110],"users.":[113],"use":[115,130],"ELA":[117],"select":[120],"composite":[125],"algorithm":[126,135],"extends":[127],"their":[128],"standard":[129],"as":[131],"part":[132],"an":[134],"selector":[136],"provides":[138],"insight":[139],"relationship":[142],"between":[143],"exploration":[144],"exploitation":[146],"types":[149],"fitness":[151]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}