{"id":"https://openalex.org/W4406612466","doi":"https://doi.org/10.1109/wsc63780.2024.10838723","title":"Importance Sampling in Optimization under Uncertainty using Surrogate Models","display_name":"Importance Sampling in Optimization under Uncertainty using Surrogate Models","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406612466","doi":"https://doi.org/10.1109/wsc63780.2024.10838723"},"language":"en","primary_location":{"id":"doi:10.1109/wsc63780.2024.10838723","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wsc63780.2024.10838723","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 Winter Simulation Conference (WSC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5001688920","display_name":"Xiaotie Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaotie Chen","raw_affiliation_strings":["University of California,Dept. of Mathematics,Davis,CA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California,Dept. of Mathematics,Davis,CA,USA","institution_ids":["https://openalex.org/I84218800"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071131174","display_name":"David L. Woodruff","orcid":"https://orcid.org/0000-0002-5902-8329"},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David L. Woodruff","raw_affiliation_strings":["Graduate School of Management, University of California,Davis,CA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Management, University of California,Davis,CA,USA","institution_ids":["https://openalex.org/I84218800"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I84218800"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.38954149,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"501","last_page":"512"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.7063999772071838,"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":0.7063999772071838,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5772356390953064},{"id":"https://openalex.org/keywords/surrogate-model","display_name":"Surrogate model","score":0.5488385558128357},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.48589128255844116},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3406394124031067},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.23756110668182373},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21974587440490723}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5772356390953064},{"id":"https://openalex.org/C131675550","wikidata":"https://www.wikidata.org/wiki/Q7646884","display_name":"Surrogate model","level":2,"score":0.5488385558128357},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.48589128255844116},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3406394124031067},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.23756110668182373},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21974587440490723},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wsc63780.2024.10838723","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wsc63780.2024.10838723","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 Winter Simulation Conference (WSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W207991364","https://openalex.org/W1569990960","https://openalex.org/W1980247637","https://openalex.org/W1981264388","https://openalex.org/W1983221302","https://openalex.org/W1983916623","https://openalex.org/W1985639525","https://openalex.org/W1995780830","https://openalex.org/W2002946775","https://openalex.org/W2009374330","https://openalex.org/W2019710194","https://openalex.org/W2021672759","https://openalex.org/W2029450231","https://openalex.org/W2038426159","https://openalex.org/W2040358553","https://openalex.org/W2078566378","https://openalex.org/W2100549100","https://openalex.org/W2112201164","https://openalex.org/W2151194818","https://openalex.org/W2160183615","https://openalex.org/W2193006036","https://openalex.org/W2532481546","https://openalex.org/W2757101479","https://openalex.org/W2811395263","https://openalex.org/W2939938231","https://openalex.org/W2986637230","https://openalex.org/W3042035870","https://openalex.org/W3093808819","https://openalex.org/W3140959975","https://openalex.org/W4245710224","https://openalex.org/W4256012597","https://openalex.org/W4292403327","https://openalex.org/W4293252510","https://openalex.org/W4379162539","https://openalex.org/W4385806759"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"For":[0],"the":[1,5,32],"purpose":[2],"of":[3,8,31,71],"computing":[4],"expected":[6],"value":[7],"a":[9,17,68],"stochastic":[10],"optimization":[11],"problem":[12],"via":[13],"simulation,":[14],"we":[15],"propose":[16],"method":[18,50,76],"for":[19,62],"efficiently":[20],"constructing":[21],"importance":[22],"sampling":[23],"distributions":[24],"using":[25],"surrogate":[26],"modeling.":[27],"A":[28],"software":[29,43],"implementation":[30],"methods":[33],"called":[34],"SMAIS":[35],"is":[36,83],"available":[37],"on":[38],"github.":[39],"We":[40,56],"use":[41],"this":[42],"in":[44],"experiments":[45],"to":[46,64,87],"demonstrate":[47],"that":[48],"our":[49],"can":[51],"outperform":[52],"Monte":[53],"Carlo":[54],"simulation.":[55],"also":[57],"show":[58],"good":[59],"parallel":[60],"efficiency":[61],"up":[63,70],"16":[65],"processors":[66],"allowing":[67],"speed":[69],"more":[72],"than":[73],"10.":[74],"Our":[75],"uses":[77],"adaptive":[78],"sample":[79,88],"sizes":[80],"so":[81],"it":[82],"not":[84],"very":[85],"sensitive":[86],"size":[89],"parameters.":[90]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
