{"id":"https://openalex.org/W3181559307","doi":"https://doi.org/10.1145/3449726.3463283","title":"Surrogate-based optimisation for a hospital simulation scenario using pairwise classifiers","display_name":"Surrogate-based optimisation for a hospital simulation scenario using pairwise classifiers","publication_year":2021,"publication_date":"2021-07-07","ids":{"openalex":"https://openalex.org/W3181559307","doi":"https://doi.org/10.1145/3449726.3463283","mag":"3181559307"},"language":"en","primary_location":{"id":"doi:10.1145/3449726.3463283","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3449726.3463283","pdf_url":null,"source":{"id":"https://openalex.org/S4363608771","display_name":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","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 Companion","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/A5015142812","display_name":"Pablo S. Naharro","orcid":"https://orcid.org/0000-0002-1213-2559"},"institutions":[{"id":"https://openalex.org/I88060688","display_name":"Universidad Polit\u00e9cnica de Madrid","ror":"https://ror.org/03n6nwv02","country_code":"ES","type":"education","lineage":["https://openalex.org/I88060688"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Pablo S. Naharro","raw_affiliation_strings":["Universidad Polit\u00e9cnica de Madrid, Madrid, Spain"],"affiliations":[{"raw_affiliation_string":"Universidad Polit\u00e9cnica de Madrid, Madrid, Spain","institution_ids":["https://openalex.org/I88060688"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030033407","display_name":"Antonio LaTorre","orcid":"https://orcid.org/0000-0002-8718-5735"},"institutions":[{"id":"https://openalex.org/I88060688","display_name":"Universidad Polit\u00e9cnica de Madrid","ror":"https://ror.org/03n6nwv02","country_code":"ES","type":"education","lineage":["https://openalex.org/I88060688"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Antonio LaTorre","raw_affiliation_strings":["Universidad Polit\u00e9cnica de Madrid, Madrid, Spain"],"affiliations":[{"raw_affiliation_string":"Universidad Polit\u00e9cnica de Madrid, Madrid, Spain","institution_ids":["https://openalex.org/I88060688"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064290966","display_name":"Jos\u00e9-Mar\u00eda Pe\u00f1a","orcid":"https://orcid.org/0000-0002-3303-0455"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jos\u00e9-Mar\u00eda Pe\u00f1a","raw_affiliation_strings":["Lurtis Ltd., Oxford, UK"],"affiliations":[{"raw_affiliation_string":"Lurtis Ltd., Oxford, UK","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5015142812"],"corresponding_institution_ids":["https://openalex.org/I88060688"],"apc_list":null,"apc_paid":null,"fwci":0.8714,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.61666667,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"15","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11773","display_name":"Healthcare Operations and Scheduling Optimization","score":0.9936000108718872,"subfield":{"id":"https://openalex.org/subfields/3604","display_name":"Emergency Medical Services"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11773","display_name":"Healthcare Operations and Scheduling Optimization","score":0.9936000108718872,"subfield":{"id":"https://openalex.org/subfields/3604","display_name":"Emergency Medical Services"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11195","display_name":"Simulation Techniques and Applications","score":0.9478999972343445,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.8246623277664185},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6717736721038818},{"id":"https://openalex.org/keywords/surrogate-model","display_name":"Surrogate model","score":0.5986490845680237},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5368573665618896},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.459212064743042}],"concepts":[{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.8246623277664185},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6717736721038818},{"id":"https://openalex.org/C131675550","wikidata":"https://www.wikidata.org/wiki/Q7646884","display_name":"Surrogate model","level":2,"score":0.5986490845680237},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5368573665618896},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.459212064743042}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3449726.3463283","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3449726.3463283","pdf_url":null,"source":{"id":"https://openalex.org/S4363608771","display_name":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","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 Companion","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.7099999785423279}],"awards":[{"id":"https://openalex.org/G7491012936","display_name":null,"funder_award_id":"IND2019/TIC-17140","funder_id":"https://openalex.org/F4320313831","funder_display_name":"Comunidad de Madrid"}],"funders":[{"id":"https://openalex.org/F4320313831","display_name":"Comunidad de Madrid","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W1678356000","https://openalex.org/W2886496608","https://openalex.org/W3112162176","https://openalex.org/W3179405117","https://openalex.org/W4389138872"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347","https://openalex.org/W4210805261"],"abstract_inverted_index":{"This":[0,30],"paper":[1],"presents":[2],"a":[3,8,14,28,34,43,70,83,92,100,105,114,136,159],"surrogate-based":[4,31],"approach":[5,94,153],"that":[6,74,95],"uses":[7,33],"relatively":[9],"simple":[10],"population-based":[11],"optimisation":[12,32,57],"algorithm,":[13],"basic":[15],"Differential":[16],"Evolution":[17],"algorithm":[18,88,108],"(DE),":[19],"and":[20,38,90,158],"experiments":[21],"with":[22,164],"two":[23],"complementary":[24,60],"approaches":[25,61],"to":[26,41,145],"construct":[27],"surrogate.":[29],"predictive":[35],"model":[36],"in-line":[37],"decides":[39],"whether":[40],"calculate":[42],"candidate":[44],"individual":[45],"(using":[46],"the":[47,56,63,66,76,79,97,126,132,141,151,155],"simulation":[48],"model)":[49],"or":[50],"discard":[51],"it":[52],"as":[53,99],"part":[54],"of":[55,65,78,128],"process.":[58],"The":[59],"for":[62,104],"design":[64],"surrogate":[67,73,98,130],"are":[68],"(1)":[69],"traditional":[71],"regression-based":[72],"approximates":[75],"surface":[77],"fitness":[80,147,166],"landscape":[81],"using":[82],"supervised":[84],"continuous":[85],"machine":[86,106],"learning":[87,107],"(XGBoost),":[89],"(2)":[91],"pairwise":[93],"models":[96],"binary":[101,117],"classification":[102],"problem":[103],"(in":[109],"this":[110],"experiment":[111],"we":[112],"proposed":[113],"Decision":[115],"Tree":[116],"classifier).":[118],"Although":[119],"there":[120],"is":[121,143],"no":[122],"statistical":[123],"difference":[124],"in":[125,162],"performance":[127,139],"both":[129],"approaches,":[131],"surface/regression":[133],"one":[134],"obtains":[135,154],"slightly":[137],"better":[138],"when":[140],"execution":[142],"limited":[144],"200":[146],"evaluations.":[148,167],"In":[149],"contrast,":[150],"pairwise/classification":[152],"lowest":[156],"value":[157],"lower":[160],"mean":[161],"executions":[163],"750":[165]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}