{"id":"https://openalex.org/W2395830116","doi":null,"title":"A Stopping Criterion for Surrogate Based Optimization using EGO","display_name":"A Stopping Criterion for Surrogate Based Optimization using EGO","publication_year":2013,"publication_date":"2013-01-01","ids":{"openalex":"https://openalex.org/W2395830116","mag":"2395830116"},"language":"en","primary_location":{"id":"mag:2395830116","doi":null,"is_oa":false,"landing_page_url":"http://www2.mae.ufl.edu/mdo/Papers/5274.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"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/A5059088770","display_name":"Anirban Chaudhuri","orcid":"https://orcid.org/0000-0002-2281-3067","observed_orcids":["https://orcid.org/0000-0002-2281-3067"]},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anirban Chaudhuri","raw_affiliation_strings":["University of Florida"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Florida","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013992441","display_name":"Raphael T. Haftka","orcid":"https://orcid.org/0000-0003-0417-6911","observed_orcids":["https://orcid.org/0000-0003-0417-6911"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Raphael T. Haftka","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-0417-6911","affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.0197,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.84784664,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":87,"max":97},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9932000041007996,"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":0.9932000041007996,"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/T10963","display_name":"Advanced Optimization Algorithms Research","score":0.001500000013038516,"subfield":{"id":"https://openalex.org/subfields/2612","display_name":"Numerical Analysis"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11195","display_name":"Simulation Techniques and Applications","score":0.00139999995008111,"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/stopping-criterion","display_name":"stopping rules","score":0.843999981880188},{"id":"https://openalex.org/keywords/surrogate-based-optimization","display_name":"surrogate-based optimization","score":0.9559999704360962},{"id":"https://openalex.org/keywords/efficient-global-optimization","display_name":"efficient global optimization","score":0.9440000057220459},{"id":"https://openalex.org/keywords/expected-improvement","display_name":"expected improvement","score":0.8889999985694885},{"id":"https://openalex.org/keywords/kriging-surrogate-model","display_name":"Kriging surrogate model","score":0.7879999876022339},{"id":"https://openalex.org/keywords/global-optimization","display_name":"global optimization","score":0.847000002861023},{"id":"https://openalex.org/keywords/design-point-selection","display_name":"design point selection","score":0.5239999890327454},{"id":"https://openalex.org/keywords/resource-allocation","display_name":"resource allocation","score":0.40400001406669617}],"concepts":[{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5902584791183472},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5718242526054382},{"id":"https://openalex.org/C131675550","wikidata":"https://www.wikidata.org/wiki/Q7646884","display_name":"Surrogate model","level":2,"score":0.5543580651283264},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.5452580451965332},{"id":"https://openalex.org/C9180747","wikidata":"https://www.wikidata.org/wiki/Q486893","display_name":"Id, ego and super-ego","level":2,"score":0.48378846049308777},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.45195502042770386},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4508122205734253},{"id":"https://openalex.org/C164752517","wikidata":"https://www.wikidata.org/wiki/Q5570875","display_name":"Global optimization","level":2,"score":0.4385855793952942},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.4156070053577423},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4033873677253723},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.17989596724510193},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.08608779311180115},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","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/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C11171543","wikidata":"https://www.wikidata.org/wiki/Q41630","display_name":"Psychoanalysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:2395830116","doi":null,"is_oa":false,"landing_page_url":"http://www2.mae.ufl.edu/mdo/Papers/5274.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W1510052597","https://openalex.org/W1616579013","https://openalex.org/W1879678483","https://openalex.org/W2144636407","https://openalex.org/W2168464387"],"related_works":["https://openalex.org/W2316778888","https://openalex.org/W2325831679","https://openalex.org/W2327116140","https://openalex.org/W2295964580","https://openalex.org/W1988696933","https://openalex.org/W2028684871","https://openalex.org/W2344245780","https://openalex.org/W2792257914","https://openalex.org/W2376095482","https://openalex.org/W2619926566"],"abstract_inverted_index":{"In":[0,158],"Surrogate-based":[1],"optimization,":[2,216],"each":[3,120],"optimization":[4,24,92,291],"cycle":[5,121,141,150,172],"consists":[6],"of":[7,14,19,55,72,97,105,235,240,271,277],"fitting":[8],"a":[9,12,17,163,182,205,219,230,233,258,287],"surrogate":[10,28,50],"to":[11,29,51,68,81,111,134,155,178,212,229],"number":[13],"simulations":[15],"at":[16,180],"set":[18],"design":[20,35],"points,":[21],"and":[22,65,124,267],"performing":[23],"based":[25,217],"on":[26,218],"the":[27,48,53,70,78,85,95,112,144,186,194,215,255,264,269,278],"obtain":[30],"one":[31,139,170],"or":[32,136],"more":[33,140,171],"new":[34,56],"points.":[36],"Algorithms":[37],"like":[38],"Efficient":[39],"Global":[40],"Optimization":[41],"(EGO)":[42],"use":[43],"uncertainty":[44],"estimates":[45],"available":[46],"with":[47,169,199,204,214,244],"Kriging":[49],"guide":[52],"selection":[54],"point(s).":[57],"The":[58,102,275],"most":[59,195],"common":[60,196],"EGO":[61,197,236],"variant":[62,198,234],"uses":[63,238],"prediction":[64,66],"variance":[67],"seek":[69],"point":[71,80],"maximum":[73],"Expected":[74],"Improvement":[75,242],"(EI)":[76],"as":[77],"next":[79,265],"be":[82],"sampled":[83],"in":[84,90,147,185,263],"optimization.":[86],"A":[87],"major":[88],"problem":[89],"global":[91,290],"has":[93,108],"been":[94,109],"lack":[96],"an":[98,245],"adequate":[99],"stopping":[100,106,164,192,279],"criterion.":[101],"traditional":[103],"goal":[104],"criteria":[107,280],"convergence":[110,125],"optimum,":[113],"but":[114],"this":[115,148,159,191],"is":[116,122,126,142,176,201,226,284],"not":[117],"practical":[118,129],"when":[119,131],"expensive":[123],"slow.":[127],"One":[128],"question":[130],"considering":[132],"whether":[133,143],"stop":[135],"carry":[137],"out":[138],"resources":[145],"invested":[146],"additional":[149],"would":[151],"yield":[152,179],"sufficient":[153],"return":[154],"justify":[156],"it.":[157],"paper":[160],"we":[161],"propose":[162],"criterion":[165,193,220],"which":[166,237],"justifies":[167],"continuing":[168],"only":[173],"if":[174],"it":[175,210],"expected":[177],"least":[181],"specified":[183,206],"improvement":[184,207,262],"objective":[187],"function.":[188],"To":[189],"implement":[190],"EI":[200],"used":[202],"along":[203],"that":[208,273],"makes":[209],"worthy":[211],"continue":[213],"suggested":[221],"by":[222],"Schonlau.":[223],"Its":[224],"efficiency":[225],"also":[227],"compared":[228],"case":[231],"using":[232,286],"Probability":[239],"targeted":[241],"(PI)":[243],"adaptive":[246],"target,":[247],"EGO-AT.":[248],"EGO-AT":[249],"provides":[250],"two":[251],"important":[252],"ingredients":[253],"for":[254,261,281],"criterion:":[256],"(i)":[257],"reasonable":[259],"target":[260],"cycle,":[266],"(ii)":[268],"probability":[270],"achieving":[272],"target.":[274],"effectiveness":[276],"both":[282],"algorithms":[283],"demonstrated":[285],"few":[288],"benchmark":[289],"problems.":[292]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":3}],"updated_date":"2026-09-21T07:43:02.447757","created_date":"2016-06-24T00:00:00"}
