{"id":"https://openalex.org/W4248679521","doi":"https://doi.org/10.1109/wsc.2018.8632169","title":"GREEN SIMULATION OPTIMIZATION USING LIKELIHOOD RATIO ESTIMATORS","display_name":"GREEN SIMULATION OPTIMIZATION USING LIKELIHOOD RATIO ESTIMATORS","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W4248679521","doi":"https://doi.org/10.1109/wsc.2018.8632169"},"language":"en","primary_location":{"id":"doi:10.1109/wsc.2018.8632169","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wsc.2018.8632169","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 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/A5029732249","display_name":"David J. Eckman","orcid":"https://orcid.org/0000-0002-6473-6434"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David J. Eckman","raw_affiliation_strings":["School of Operations Research and Info Engrg, Cornell University, Ithaca, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Operations Research and Info Engrg, Cornell University, Ithaca, NY, USA","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018292361","display_name":"Miaomiao Feng","orcid":"https://orcid.org/0009-0008-0190-5107"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"M. Ben Feng","raw_affiliation_strings":["Dept of Statistics and Actuarial Science, University of Waterloo, Waterloo, ON, CANADA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept of Statistics and Actuarial Science, University of Waterloo, Waterloo, ON, CANADA","institution_ids":["https://openalex.org/I151746483"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9529,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.75730296,"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":"2049","last_page":"2060"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9796000123023987,"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":0.9796000123023987,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9735999703407288,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.97079998254776,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.8484683036804199},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6057949066162109},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5920049548149109},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5060021281242371},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.4560910761356354},{"id":"https://openalex.org/keywords/computer-simulation","display_name":"Computer simulation","score":0.440384179353714},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.25921112298965454},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2553831934928894},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.16219913959503174}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.8484683036804199},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6057949066162109},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5920049548149109},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5060021281242371},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.4560910761356354},{"id":"https://openalex.org/C500300565","wikidata":"https://www.wikidata.org/wiki/Q925667","display_name":"Computer simulation","level":2,"score":0.440384179353714},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.25921112298965454},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2553831934928894},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.16219913959503174},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wsc.2018.8632169","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wsc.2018.8632169","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Winter Simulation Conference (WSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4287880334","https://openalex.org/W4366700029","https://openalex.org/W4285230481","https://openalex.org/W4385769873","https://openalex.org/W4281634296","https://openalex.org/W4319161863","https://openalex.org/W2371687270","https://openalex.org/W4311888330","https://openalex.org/W2517641583","https://openalex.org/W4221071877"],"abstract_inverted_index":{"Green":[0],"simulation":[1,7,17,24,30,58,66,107],"is":[2,25],"the":[3,11,27,93,96,99,112,130],"reuse":[4],"of":[5,13,22,29,92,98,111,132],"past":[6,35,81],"outputs":[8,33,83],"to":[9,52],"enhance":[10],"efficiency":[12],"current":[14],"and":[15,114,125],"future":[16],"experiments.":[18],"One":[19],"natural":[20],"application":[21],"green":[23,57,106],"in":[26,37,43,65,84],"context":[28],"optimization,":[31],"wherein":[32],"from":[34],"iterations":[36,86],"a":[38,104],"search":[39],"can":[40,116,127],"be":[41],"reused":[42],"subsequent":[44],"iterations.":[45],"In":[46,68],"this":[47,122],"article,":[48],"we":[49,70],"draw":[50],"attention":[51],"challenges":[53],"that":[54,72,75],"arise":[55],"when":[56],"likelihood":[59,100,108],"ratio":[60,101,109],"estimators":[61,110],"are":[62,87],"naively":[63],"employed":[64],"optimization.":[67],"particular,":[69],"show":[71],"for":[73,95],"searches":[74],"identify":[76],"new":[77],"designs":[78],"based":[79],"on":[80],"outputs,":[82],"different":[85],"conditionally":[88],"dependent,":[89],"violating":[90],"one":[91],"assumptions":[94],"validity":[97],"estimator.":[102],"As":[103],"result,":[105],"objective":[113],"gradient":[115],"become":[117],"biased.":[118],"We":[119],"demonstrate":[120],"how":[121],"conditional":[123],"dependence":[124],"bias":[126],"adversely":[128],"affect":[129],"behavior":[131],"gradient-based":[133],"optimization":[134],"algorithms.":[135]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}