{"id":"https://openalex.org/W4250371032","doi":"https://doi.org/10.1109/wsc.2017.8247939","title":"Multi-fidelity simulation optimization with level set approximation using probabilistic branch and bound","display_name":"Multi-fidelity simulation optimization with level set approximation using probabilistic branch and bound","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W4250371032","doi":"https://doi.org/10.1109/wsc.2017.8247939"},"language":"en","primary_location":{"id":"doi:10.1109/wsc.2017.8247939","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wsc.2017.8247939","pdf_url":null,"source":{"id":"https://openalex.org/S4363607803","display_name":"2017 Winter Simulation Conference (WSC)","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":"2017 Winter Simulation Conference (WSC)","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/A5034523672","display_name":"David D. Linz","orcid":null},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"David D. Linz","raw_affiliation_strings":["Department of Industrial and Systems Engineering, University of Washington, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100732402","display_name":"Hao Huang","orcid":"https://orcid.org/0000-0003-3998-9074"},"institutions":[{"id":"https://openalex.org/I99908691","display_name":"Yuan Ze University","ror":"https://ror.org/01fv1ds98","country_code":"TW","type":"education","lineage":["https://openalex.org/I99908691"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Hao Huang","raw_affiliation_strings":["Department of Industrial Engineering and Management, Yuan Zu University, Taoyuan City, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering and Management, Yuan Zu University, Taoyuan City, Taiwan","institution_ids":["https://openalex.org/I99908691"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056796690","display_name":"Zelda B. Zabinsky","orcid":"https://orcid.org/0000-0003-1838-4981"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zelda B. Zabinsky","raw_affiliation_strings":["Department of Industrial and Systems Engineering, University of Washington, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5034523672"],"corresponding_institution_ids":["https://openalex.org/I201448701"],"apc_list":null,"apc_paid":null,"fwci":0.9792,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.75110132,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"1","issue":null,"first_page":"2057","last_page":"2068"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11195","display_name":"Simulation Techniques and Applications","score":0.9988999962806702,"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"}},"topics":[{"id":"https://openalex.org/T11195","display_name":"Simulation Techniques and Applications","score":0.9988999962806702,"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"}},{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9979000091552734,"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/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.9909999966621399,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"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/probabilistic-logic","display_name":"Probabilistic logic","score":0.7096878290176392},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6185574531555176},{"id":"https://openalex.org/keywords/branch-and-bound","display_name":"Branch and bound","score":0.5994809865951538},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5748763680458069},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.5262980461120605},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5162408351898193},{"id":"https://openalex.org/keywords/approximation-algorithm","display_name":"Approximation algorithm","score":0.436184823513031},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.42364105582237244},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.33126741647720337},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2384204864501953},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23022595047950745},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.06689020991325378}],"concepts":[{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.7096878290176392},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6185574531555176},{"id":"https://openalex.org/C93693863","wikidata":"https://www.wikidata.org/wiki/Q897659","display_name":"Branch and bound","level":2,"score":0.5994809865951538},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5748763680458069},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.5262980461120605},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5162408351898193},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.436184823513031},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42364105582237244},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33126741647720337},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2384204864501953},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23022595047950745},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.06689020991325378},{"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:10.1109/wsc.2017.8247939","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wsc.2017.8247939","pdf_url":null,"source":{"id":"https://openalex.org/S4363607803","display_name":"2017 Winter Simulation Conference (WSC)","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":"2017 Winter Simulation Conference (WSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.4300000071525574,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1979308183","https://openalex.org/W1982886636","https://openalex.org/W2095658148","https://openalex.org/W2124548165","https://openalex.org/W2397089707","https://openalex.org/W2471978209","https://openalex.org/W4230425707","https://openalex.org/W4236367639","https://openalex.org/W4237169171","https://openalex.org/W4238943717","https://openalex.org/W4255693858","https://openalex.org/W6696792689"],"related_works":["https://openalex.org/W2381850946","https://openalex.org/W4380449851","https://openalex.org/W3125091513","https://openalex.org/W4318832338","https://openalex.org/W1919390113","https://openalex.org/W4248383205","https://openalex.org/W4234745530","https://openalex.org/W1497573972","https://openalex.org/W2071659383","https://openalex.org/W1846253165"],"abstract_inverted_index":{"Simulated":[0],"systems":[1],"are":[2,90],"often":[3],"described":[4],"with":[5,41],"a":[6,42,59,66,70,82,98,128],"variety":[7],"of":[8,10,15,32,37,45,65,97,106,123,140],"models":[9,24],"different":[11],"complexity.":[12],"Making":[13],"use":[14,20],"these":[16],"models,":[17],"algorithms":[18],"can":[19],"low":[21],"complexity,":[22],"\u201clow-fidelity\u201d":[23],"or":[25],"meta-models":[26],"to":[27,80,92,147],"guide":[28],"sampling":[29,124],"for":[30,56,85],"purposes":[31],"optimization,":[33],"improving":[34],"the":[35,54,63,74,86,104,120,138,141],"probability":[36,122],"generating":[38],"good":[39],"solutions":[40,57,95,126],"small":[43],"number":[44,105],"observations.":[46],"We":[47,132],"propose":[48],"an":[49,115],"optimization":[50],"algorithm":[51,79,116],"that":[52,136],"guides":[53],"search":[55],"on":[58],"high-fidelity":[60,107],"model":[61],"through":[62],"approximation":[64,145],"level":[67,83,130,143],"set":[68,84,144],"from":[69],"low-fidelity":[71,87,129],"model.":[72],"Using":[73],"Probabilistic":[75],"Branch":[76],"and":[77,101,117],"Bound":[78],"approximate":[81],"model,":[88],"we":[89],"able":[91],"efficiently":[93],"locate":[94,148],"inside":[96],"target":[99],"quantile":[100],"therefore":[102],"reduce":[103],"evaluations":[108],"needed":[109],"in":[110],"searches.":[111],"The":[112],"paper":[113],"provides":[114],"analysis":[118],"showing":[119],"increased":[121],"high-quality":[125],"within":[127],"set.":[131],"include":[133],"numerical":[134],"examples":[135],"demonstrate":[137],"effectiveness":[139],"multi-fidelity":[142],"method":[146],"solutions.":[149]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}